Abstract

Systems and methods for deep technology innovation management by cross- pollinating innovations dataset are disclosed. A system extracts context-based keyword from an innovation dataset by transforming the innovation dataset to a vector. Further, the system searches semantically relevant keywords for the extracted context-based keyword, by extracting an entity and a key phrase from the extracted a context-based keyword. Furthermore, system clusters the vector, by identifying frequent keywords in the semantically relevant keywords to obtain cluster centroids of the frequent keywords. Thereafter, the system determines weighted keywords in each cluster using the obtained cluster centroids, and classifies the weighted keywords to identify emerging innovation trends relevant to the innovation in the innovation dataset. The system forms cohorts of innovators to explore the reuse of innovations, assets, code, and build focused monetization model.

IPC Classes  ?

• G06F 18/20 - Analysing
• G06F 40/205 - Parsing
• G06F 40/295 - Named entity recognition
• G06F 40/30 - Semantic analysis
• G06F 18/213 - Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
• G06F 18/23 - Clustering techniques
• G06F 18/24 - Classification techniques
• G06Q 10/0637 - Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• G06N 5/02 - Knowledge representation; Symbolic representation

Abstract

Systems and methods for evaluating attributes in supply chain management is disclosed. The system may receive data from a set of data sources corresponding to a supply chain associated with at least a product, pre-process the data based on integration of the data from each of the set of data sources, generate supply chain data based on the integrated data, analyze, via an orchestration engine, the supply chain data to assess an impact of the supply chain data on the supply chain, predict, via the orchestration engine, a state associated with a purchase event of the product in the supply chain, and generate a resolution flow to be executed in the supply chain for managing the predicted state associated with the purchase event of the product.

IPC Classes  ?

• G06Q 10/087 - Inventory or stock management, e.g. order filling, procurement or balancing against orders
• G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"

Abstract

This document describes a computer-implemented method that includes receiving, over a network, at least one of text, audio, image, or video data associated with an entity of interest; identifying, based on the received data, a set of entity-specific candidate features; loading a feature library comprising a plurality of features that are each assigned to one or more feature spaces; and selecting, using a feature selection engine, one or more features from each of the feature spaces based on the set of entity-specific candidate features.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
• G06N 20/00 - Machine learning
• G06F 40/279 - Recognition of textual entities
• G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations

Abstract

Aspects of the present disclosure provide systems, methods, and computer- readable storage media that support creation and execution of automated sequences of user interface (UI) interactions. To facilitate creation and execution of automated sequences of UI interactions, an automation engine is provided and includes a model configured to capture image data when creating the sequence of UI interactions. The model may also be used during replay of the sequence of UI interactions. For example, the model may be used during replay of the sequence of UI interactions to locate UI elements corresponding to the UI interactions, or to perform pre- and/or post-validation of action execution. The automation engine may also provide processes to enable location of dynamic content, such as UI elements that may be presented in different or unexpected locations, and processes to address complex UI elements, such as data grids, tree views, and drawings (e.g., CAD drawings).

IPC Classes  ?

• G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
• G06N 20/00 - Machine learning
• G06V 30/40 - Document-oriented image-based pattern recognition
• G06N 3/0464 - Convolutional networks [CNN, ConvNet]
• G06F 30/12 - Geometric CAD characterised by design entry means specially adapted for CAD, e.g. graphical user interfaces [GUI] specially adapted for CAD

Abstract

An Artificial Intelligence (Al) based data processing system transforms a plurality of time series data sets for processing by one or more deep learning (DL) models for generating forecasts. The DL models are initially trained on training data generated from the historical data. During operation, a plurality of transformed time series data sets are generated from the plurality of time series data sets associated with different entities in an entity hierarchy via data flattening and data stacking. A primary model of the one or more DL models is trained on first-party data for generating the forecasts. An extended model of the one or more DL models is trained on third-party data from external data sources. Whenever new data is available in the first-party data or the third-party data, the primary model and the extended model are correspondingly updated.

IPC Classes  ?

• G06N 3/04 - Architecture, e.g. interconnection topology
• G06N 3/08 - Learning methods
• G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"

Abstract

Unified, cross-channel, multidimensional insight generation is presented according to embodiments of the present invention. Embodiments include receiving communications between a business development representative (13DR') and a customer across disparate communications channels, each channel comprising a channel type, channel communications protocol, and channel form; normalizing the disparate communications in dependence upon nomialization rules; summarizing the nomialized communications in dependence upon summarization rules; creating semantic triples in dependence upon the summarized and normalized communications including applying a sales-progress-directed taxonomy and ontology; creating a multidimensional vector in dependence upon the semantic triples; wherein the multidimensional vector includes one or more attributes of a sales cycle; and identifying one or more insights in dependence upon the multidimensional vector.

Abstract

Methods and systems for dynamic dashboard administration are presented. Embodiments include displaying a dashboard through a graphical user interface (GUI'); receiving user instructions to manipulate one or more elements of the dynamic dashboard; capturing the manipulation of the one or more GUI elements; parsing, according to a gesture taxonomy and gesture ontology, the captured manipulation into one or more gesture triples; storing the gesture triples in an enterprise knowledge graph of a semantic graph database; identifying, in dependence upon the gesture triples, dashboard insights; updating the dashboard in accordance with the dashboard insights.

IPC Classes  ?

• G06Q 10/063 - Operations research, analysis or management
• 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
• G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
• G06Q 30/01 - Customer relationship services
• G06F 3/16 - Sound input; Sound output

Abstract

A knowledge graph based reasoning recommendation system and method may analyze past concluded legal cases to find patterns and predict the outcomes of new legal cases before or during litigation. These patterns and outcomes may be used to determine a recommendation for a legal strategy. Input documents and/or enterprise claim data from past concluded cases may be combined and processed to calculate an association rule for the legal outcome associated with one or more of the claim type, counsel, and judge for the group of similar cases based on the analysis of individual cases within the group. Features extracted from the input documents from the past concluded cases and the calculated association rules may be incorporated into a knowledge graph, along with features extracted from input documents from new legal cases. A Policy-Guided Path Reasoning (PGPR) may be applied over the knowledge graph to calculate which legal strategy to recommend. The recommended legal strategy, as well as the reasoning for recommending the legal strategy may be displayed to a user.

IPC Classes  ?

• G06Q 50/18 - Legal services; Handling legal documents

Abstract

A system of monitoring and optimizing computing resources usage for computing application may include predicting a first performance metric for job load capacity of a computing application for optimal job concurrency and optimal resource utilization. The system may include generating an alerting threshold based on the first performance metric. The system may further include, in response to a difference between the alerting threshold and a job load of the computing application within an interval exceeding a threshold, predicting a second performance metric for job load capacity of the computing application for optimal job concurrency and optimal resource utilization. The system may further include, in response to a difference between the first performance metric and the second performance metric exceeding a difference threshold, updating the alerting threshold with a job load capacity with the optimal resource utilization rate corresponding to the second performance metric.

IPC Classes  ?

• G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
• G06F 11/30 - Monitoring

Abstract

A system for providing temporary, transportable cellular communications networks is disclosed. The system includes at least one mobile base station and a control system. The mobile base station can include an aerial vehicular base station with a frame and propellers mounted on the frame that enable flight of the aerial vehicular base station while the control system is configured to control the flight path and functioning of the aerial vehicular base station. The aerial vehicular base station includes hardware and software components for providing cellular network coverage for short ranges. The control system determines the safe flight path for the aerial vehicular base station to reach a service location to provide cellular network coverage. The aerial vehicular base station identifies the closest base stations and available spectrum at the service location to provide communication services for the user equipment at the service location.

IPC Classes  ?

• H04W 84/06 - Airborne or Satellite Networks
• H04W 88/08 - Access point devices
• G08G 5/00 - Traffic control systems for aircraft
• H04W 16/18 - Network planning tools

Abstract

In some implementations, a device may receive prescription information associated with a medication in a container. The device may cause a camera to capture first image data associated with the medication while the medication is in the container and the container is positioned on a receptacle. The device may cause an adjusting device to reposition the container on the receptacle. The device may cause the camera to capture second image data associated with the medication while the medication is in the container. The device may process, via a neural network, the first image data and the second image data to identify the medication based on depictions of individual units of the medication included in the first image data and the second image data. The device may verify the medication based on the prescription information and an identifier of the medication provided by the neural network.

IPC Classes  ?

• G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06N 3/02 - Neural networks

Abstract

Systems and methods are provided for the classification of identified security vulnerabilities in software applications, and their triage based on automated decision-tree triage and/or machine learning. The disclosed system may generate a report listing detected potential vulnerability issues, and automatically determine whether the potential vulnerability issues are exploitable using automated triage policies containing decision trees or by extracting vulnerability features from the report and processing the extracted vulnerability features using machine learning models.

IPC Classes  ?

• 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

Abstract

A device may generate a registration mapping that associates a client identifier of a media client and a messaging identifier of a user device. The device may store the registration mapping in a registration data structure. The device may receive, via a messaging protocol, a message from the user device. The message may include the message identifier and an input for an application session of the media client. The device may determine, based on the registration data structure including the registration mapping and the message, that the user device is associated with the media client. The device may provide, via the messaging protocol, the message to the media client to permit the application session to operate according to the input.

IPC Classes  ?

• H04N 21/6547 - Transmission by server directed to the client comprising parameters, e.g. for client setup
• H04N 21/40 - Client devices specifically adapted for the reception of, or interaction with, content, e.g. STB [set-top-box]; Operations thereof
• H04N 21/6334 - Control signals issued by server directed to the network components or client directed to client for authorisation, e.g. by transmitting a key
• H04N 21/643 - Communication protocols
• H04N 21/658 - Transmission by the client directed to the server

Abstract

A model optimization system monitors a model deployed to an external system to determine the performance of the model and to replace the model with one of a plurality of models stored to a model repository if degradation of model performance is detected or if one of the models in the plurality of models is evaluated as having better performance than the model deploy the external system. A model evaluation trigger can be generated based on dates or data criteria. Various metrics are used in the model evaluation to calculate values of a model optimization function for each of the plurality of models. If a model that is better optimized than the deployed model is identified from the model evaluation, then the deployed model is replaced with the identified model and the external system continues to use the deployed model.

IPC Classes  ?

• G06N 20/00 - Machine learning

Abstract

An utterance recommendation system may obtain a plurality of utterance influencing attributes influencing a response recommended for a user query from a plurality of sources. The system may collate the utterance influencing attributes to provide enriched user data and may identify a set of preconfigured potential utterance options associated with the user query. The system may implement a plurality of utterance recommendation techniques to analyze the enriched user data based on associated predefined rules, and provide a preferential rank ordering of the preconfigured potential utterance options to be recommended based on the analysis. The system may determine a single optimized rank ordering of the preconfigured potential utterance options representing a ranking order of the preconfigured potential utterance options. The system may provide the response to the user query, based on a potential utterance option ranked highest in the single optimized rank ordering.

IPC Classes  ?

• G06F 40/35 - Discourse or dialogue representation

Abstract

Aspects of the present disclosure provide an environmental probe configured to be at least partially inserted into the ground at a location and to provide defensible space monitoring and maintenance for a home or other structure. The environmental probe may include one or more environmental sensors configured to perform various environmental measurements to generate environmental measurement data. The environmental probe (e.g., a processor of the environmental probe) may compare the environmental measurement data to one or more thresholds to determine an alert state associated with the location. The environmental probe may include one or more wireless interfaces configured to enable communication with a remote device, such as a smart hub device or other environmental probes. The environmental probe may transmit an indicator of the alert state to the remote device to enable performance of one or more operations based on the alert state.

IPC Classes  ?

• G01D 21/00 - Measuring or testing not otherwise provided for
• A62C 3/00 - Fire prevention, containment or extinguishing specially adapted for particular objects or places
• G01D 21/02 - Measuring two or more variables by means not covered by a single other subclass
• G08B 21/12 - Alarms for ensuring the safety of persons responsive to undesired emission of substances, e.g. pollution alarms
• G08C 17/02 - Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
• H04W 4/38 - Services specially adapted for particular environments, situations or purposes for collecting sensor information
• G01D 7/00 - Indicating measured values

Abstract

An Artificial Intelligence (Al) based document processing system receives a request including one or more of a message and documents related to a process to be automatically executed. A process identifier is extracted and used for retrieving guidelines for the automatic execution of the document processing task. Machine Learning (ML) models, each corresponding to a guideline, are used to extract data responsive to the guidelines. Based on the responsive data meeting the approval threshold and the automatic document processing task executed, one or more of a recommendation to accept or reject the request, and a corresponding letter can be automatically generated.

IPC Classes  ?

• G06F 40/20 - Natural language analysis
• G06Q 40/08 - Insurance
• G06N 3/02 - Neural networks

Abstract

A mobile unit that includes a compressed gas canister, a brake hose coupled to the compressed gas canister, a radar, and a processor and a storage device. The storage device stores instructions that are operable, when executed by the processor, to cause the processor to perform operations of obtaining radar data from the radar, determining, based on the radar data, a distance of the mobile unit to an object, determining that the distance of the mobile unit to the object satisfies a braking criteria, and based on determining that the distance of the mobile unit to the object satisfies the braking criteria, releasing gas from the compressed gas canister through the brake hose coupled to the compressed gas canister and into the brake pipe of a train car.

IPC Classes  ?

• B61H 13/00 - Actuating rail-vehicle brakes
• B61H 11/02 - Applications or arrangements of braking or retarding apparatus not otherwise provided for; Combinations of apparatus of different kinds or types of self-applying brakes

Abstract

The present disclosure relates to a system, a method, and a product for an artificial intelligence based virtual agent trainer. The system includes a processor in communication with a memory storing instructions. When the processor executes the instructions, the instructions are configured to cause the processor to obtain input data and generate a preliminary set of utterances based on the input data, process the preliminary set of utterances to generate a set of utterance training data, generate a set of conversations based on the set of utterance training data, simulate the set of conversations on a virtual agent to obtain a conversation result, verify an intent and a response based on the conversation result, verify a use case flow and flow hops based on the conversation result, and generate recommendation information and maturity report based on verification results.

IPC Classes  ?

• G10L 13/027 - Concept to speech synthesisers; Generation of natural phrases from machine-based concepts
• G10L 13/08 - Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination
• G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog

Abstract

A system and method for improving outcomes in various person-to-person goal- oriented interactions is disclosed. Specifically, the method and system enable intelligent insights and recommendations to be presented to a facilitator of the interaction via a virtual assistant user interface. When the facilitator seeks to produce a specific goal with respect to the participant, the system can be configured to automatically generate, based on a series of inputs about the participant and previous interactions, intelligent recommendations that have a high likelihood of successfully promoting the target goal in the current scenario.

IPC Classes  ?

• G06F 16/903 - Querying
• G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G10L 15/26 - Speech to text systems

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for information extraction using natural language processing. One of the methods includes determining, for one or more tokens from a plurality of tokens that represent an unstructured sentence, a token type from a plurality of predetermined token types that indicates an element type for a phrase that corresponds to the token and has one or more properties using dependency data and a part-of-speech label for the token; assigning, for a token whose associated dependency data indicates that the token has a child, data for the child token to one of the one or more properties for the token type of the token; and providing, for use by a downstream semantic system and for the token, a textual representation of the phrase for the token and the phrases for one or more of the child tokens.

IPC Classes  ?

• G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
• G06F 40/30 - Semantic analysis

Abstract

A mechanism automatically reconfigures and later restores the network configuration and settings for network devices installed at one location according to configuration and settings of corresponding network devices installed at another location. This enables a user to access these network devices the same way in both locations. This mechanism further avoids having to perform any network reconfiguration of mobile devices that may be carried between the two locations.

IPC Classes  ?

• H04L 41/084 - Configuration by using pre-existing information, e.g. using templates or copying from other elements
• H04L 41/0816 - Configuration setting characterised by the conditions triggering a change of settings the condition being an adaptation, e.g. in response to network events
• H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system

Abstract

A system access a session profile. The session profile may include log source identifiers and model identifiers. The system may deploy a log projection session based on the session profile. The system may receive, in response to deployment of the log projection session, a log stream from a log source corresponding to at least one of the log identifiers. The system may generate a log projection stream based on the log stream and an initial machine-learning model. The system may calibrate the session profile and select an alternative machine-learning model based on model performance metrics. The system may redeploy the log projection session based on the calibrated session profile. The system may automatically scale computer resources for improved job performance based on forecasted log information derived from the selected machine-learning model.

IPC Classes  ?

• G06N 20/00 - Machine learning
• G06F 11/30 - Monitoring

Abstract

A device may receive an image stream of an environment of an electronic display. The device may detect that a target is in the environment, wherein the target is detected based on the image stream including an image associated with the target. The device may identify that a first object is associated with the target, wherein the first object is identified based on the object recognition model being trained to recognize the first object. The device may determine a characteristic of the first object and may determine that a second object is in the environment. The device may generate content that is to be displayed via the electronic display, wherein the content is generated based on the characteristic of the first object and a characteristic of the second object. The device may cause the content to be displayed via the electronic display to permit the target to access the content.

IPC Classes  ?

• G06V 20/54 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
• G06V 20/10 - Terrestrial scenes
• G09F 9/30 - Indicating arrangements for variable information in which the information is built-up on a support by selection or combination of individual elements in which the desired character or characters are formed by combining individual elements

Abstract

A machine learning (ML) based automated search system receives an entity information document including a plurality of entities and identifies new entities that are similar to the plurality of entities which are not included in the entity information document via automated searches. Entity intelligence reports are generated for the plurality of entities which are further used to extract search terms. The search terms are used for executing automatic searches for documents with relevant portions. The documents are further analyzed to identify other, new entities which are not included in the entity information document. Entity intelligence reports including information regarding the new entities are also generated. Significant attributes are determined for the entities. The significant attributes are further employed in ranking the new entities so that top ranked new entities are identified. Alerts can be generated based on the information regarding the new entities.

IPC Classes  ?

• G06N 20/00 - Machine learning
• G06F 16/903 - Querying
• G06F 16/953 - Querying, e.g. by the use of web search engines

Abstract

A device may receive input data associated with a legal regulation, and may process the input data to generate a record that includes: the input data in a knowledge representation format and a semantic representation format, data identifying a feature, data identifying an industry classification, or data identifying an entity of interest. The device may process the record, with machine learning models, to determine output data that includes: data indicating that the legal regulation is inconsistent, data indicating that the legal regulation is outdated, data indicating a sentiment for the legal regulation, data indicating a prescriptive nature of the legal regulation, data indicating a complexity of the legal regulation, data indicating a misrepresentation in the legal regulation, data indicating a compliance burden associated with the legal regulation, or data indicating an industry performance impact of the legal regulation. The device may perform actions based on the output data.

IPC Classes  ?

• G06Q 50/18 - Legal services; Handling legal documents
• G06N 20/00 - Machine learning
• G06F 40/30 - Semantic analysis

Abstract

A piping and instrumentation planning and maintenance system includes an input/output (I/O) interface for receiving a target piping and instrumentation diagram (PID) from a document source system; a processor in communication with the I/O interface; and non- transitory computer readable media in communication with the processor. The non- transitory computer readable media store instruction code, which when executed by the processor, causes the processor to classify entities and properties thereof within the target PID. The entities include one or more assets and interconnections therebetween specified in the PID. The processor compares the classified entities to a knowledge base that represents relationships between a plurality of assets and interconnections between the assets. The processor then determines, based on the comparison, whether the assets in the target PID are interconnected correctly. When the assets are not interconnected correctly, the processor generates a report to identify the assets that are not interconnected correctly. The report facilitates proactive replacement or rearrangement of assets in a facility associated with the target PID.

IPC Classes  ?

• G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
• G06F 16/906 - Clustering; Classification
• G06Q 10/20 - Administration of product repair or maintenance
• G06N 5/00 - Computing arrangements using knowledge-based models

Abstract

An infrastructure deployment platform may receive configuration data relating to a plurality of devices included as components of a system, or a system of systems. The infrastructure deployment platform may process the configuration data, and may determine contextual information concerning the plurality of devices based on processing the configuration data. The contextual information may identify communicative relationships or associations between the plurality of devices. The infrastructure deployment platform may define an organizational structure of a network for the plurality of devices. The organizational structure may constrain communications between the plurality of devices based on the communicative relationships or associations. The infrastructure deployment platform may transmit the contextual information or data regarding the organizational structure to a network infrastructure controller device. The infrastructure deployment platform may perform an action to cause the network to be deployed based on the functional responsibility of the system and/or system of systems.

IPC Classes  ?

• G05B 19/042 - Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
• H04L 41/0803 - Configuration setting
• H04L 41/0853 - Retrieval of network configuration; Tracking network configuration history by actively collecting configuration information or by backing up configuration information
• H04L 41/0893 - Assignment of logical groups to network elements
• H04L 41/12 - Discovery or management of network topologies
• H04L 41/14 - Network analysis or design
• H04L 67/30 - Profiles
• H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Abstract

A device may receive a widget template of a widget. The widget template may include information relating to one or more fields of the widget and content for the one or more fields. The device may receive a stylesheet of the widget. The stylesheet may include information relating to respective style identifiers of the one or more fields. The device may generate a markup object of the widget based on the widget template. The markup object may include respective markup object entries for populating the one or more fields with the content. The device may assign the respective style identifiers to the respective markup object entries, and cause an action to be performed in connection with the markup object.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 16/22 - Indexing; Data structures therefor; Storage structures
• G06F 16/24 - Querying

Abstract

An Al-based rule generation system generates an ontology from user-provided information and further enables generating rules that govern processes via drag-and-drop operations by automatically generating code in the backend. The rule generation system after generating the ontology, provides access to the entities of the ontology via a drag-and-drop GUI which also includes operators required to generate the rules. The user can drag-and-drop the entity elements and the operator elements as needed onto a whitespace in addition to providing the requisite values in order to generate a rule flow. The rule flow is validated and published to an execution server for use by downstream processes. The rule generation system further includes custom functions in addition to enabling distributed knowledge base processes for generating the rules.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06F 3/0486 - Drag-and-drop

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for natural language control of web browsers. The methods, systems, and apparatus include actions of obtaining a query from a user, determining a likely intent and an entity from the query, determining an action and script metadata based on the likely intent and the entity, compiling scripts based on the action and the script metadata, and providing the scripts to a web browser for execution.

IPC Classes  ?

• G06F 16/953 - Querying, e.g. by the use of web search engines
• G06F 16/954 - Navigation, e.g. using categorised browsing

Abstract

A device may obtain identification information concerning a clinical trial, and may obtain, based on the identification information, selection information concerning the clinical trial and input information concerning the clinical trial. The device may select at least one machine learning model, of a plurality of machine learning models, based on the selection information, and may process, using the at least one machine learning model, the input information to determine predicted rate of recruitment (RoR) information concerning the clinical trial.

IPC Classes  ?

• G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
• G06N 20/00 - Machine learning

Abstract

A data platform may receive data files from an electronic data interchange (EDI). The data files may be received in multiple different data formats. The data platform may convert the data files to a common data format, extract data elements from the data files converted to the common data format, and assign the data elements extracted from the data files to file identifiers. The data platform may assign the data elements extracted from the data files to attribute identifiers that identify types of data represented by the data elements, aggregate the data elements to create a standardized data set, and map the data elements in the standardized data set to functions. The data platform may generate values based on mapping the data elements to the functions, determine a metric based on combining the values according to a metric definition, and post the metric to the EDI for consumption.

IPC Classes  ?

• G16H 10/00 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data
• G06F 16/23 - Updating
• H04L 12/16 - Arrangements for providing special services to substations

Abstract

A device trains a machine learning model with historical productivity data and skills data to generate a trained machine learning model that determines allocations of tasks to workers. The device receives new task data identifying new tasks to allocate to the workers and performs natural language processing on the new task data to convert the new task data to processed new task data. The device receives, from sensors associated with the workers, real- time productivity data identifying productivity of the workers in completing current tasks assigned to the workers. The device processes the processed new task data and the real-time productivity data, with the trained machine learning model, to determine allocations of the new tasks to the workers, and causes the new tasks to be allocated to the workers by one or more devices and based on the determined allocations of the new tasks.

IPC Classes  ?

• G06N 20/00 - Machine learning

Abstract

A classifier receives policy data corresponding to a new policy. Further, the classifier processes the policy data to classify the policy data into an obligation class and an informational class. An information extractor then extracts metadata from the policy data that is classified into the obligation class. Subsequently, a data translator determines if there is an incremental change in the policy data based on a comparison of the policy data with policy data corresponding to existing policies. On determining the incremental change in the policy data, the data translator translates the policy data that is classified into the obligation class into a rule based on the metadata. A rules engine then receives the rule from the data translator for claims adjudication.

IPC Classes  ?

• G06F 16/906 - Clustering; Classification
• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• G06N 20/00 - Machine learning
• G06F 7/00 - Methods or arrangements for processing data by operating upon the order or content of the data handled

Abstract

A system may facilitate distributed ledger technology (DLT) record based (for example, blockchain-based) voting. A node configured to support a voter role may access a DLT record to determine answers and/or parameters for a ballot. An organizer of the ballot may provide the voter with a voter token that confers vote- value to the voter. The voter may distribute the vote-value to the answers using committed tokens that bind the voter to a particular vote-value without divulging the particular vote value while in a cryptographic form. The voter may distribute committed tokens to multiple answers. In some cases, the distribution of the committed tokens to multiple answers may frustrate attempts to determine the one or more targets to which the voter delivers a non-null vote-value.

IPC Classes  ?

• G07C 13/00 - Voting apparatus
• H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system

Abstract

A device may receive video of a facility from an image capture system. The video may show an individual within the facility, an object within the facility, or an activity being performed within the facility. The device may process the video using a technique to identify the individual within the facility, the object within the facility, or the activity being performed within the facility. The device may track the individual, the object, or the activity through the facility to facilitate an analysis of the individual, the object, or the activity. The device may perform the analysis of the individual, the object, or the activity using information related to tracking the individual, the object, or the activity. The device may perform an action related to the individual, the object, or the activity based on a result of the analysis. The action may positively impact operations of the facility.

IPC Classes  ?

• G08B 13/196 - Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
• G06T 7/00 - Image analysis
• G06T 7/20 - Analysis of motion
• H04N 7/18 - Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
• H04N 21/80 - Generation or processing of content or additional data by content creator independently of the distribution process; Content per se

Abstract

Implementations are directed to receiving delivery order data for delivery of the tangible asset, the delivery order data including a unique identifier associated with a mobile device of a recipient, receiving evidence data from the mobile device of the recipient, providing an order record stored in a distributed ledger system, the order record including at least a portion of the delivery order data, and the evidence data, determining that the tangible asset is to be handed over to the recipient, and in response: collecting delivery evidence data, providing the delivery evidence data for comparison to the evidence data, and receiving a validation result based on the comparison, and selectively indicating that the tangible asset has been handed over to the recipient at least partially based on the validation result, and updating the order record stored in the distributed ledger system.

IPC Classes  ?

• H04W 4/35 - Services specially adapted for particular environments, situations or purposes for the management of goods or merchandise

Abstract

A system for processing a digital transaction includes a user authenticator, a processor in communication with the user authenticator, and non-transitory computer readable media that stores instruction code. The user authenticator is configured to receive biometric data associated with a user from a sensor. The sensor corresponds to at least one of: an image sensor, a finger print sensor, a motion sensor, a user interaction pattern sensor, and an infrared image sensor. The user authenticator is further configured to receive user identifying information and to determine whether the biometric data associated with the user is associated with the user identifying information to thereby validate the user. If the user is validated, the user authenticator is configured to generate user credentials associated with the user. The instruction code is executed by the processor and causes the processor to receive, from a user terminal, the user credentials. If the user credentials are valid, the processor determines different categories of information required to process the digital transaction; determines one or more data source systems that store information related to the different categories of information and the user identifying information; aggregates, from one or more data source systems, the information associated with the user identifying information; and communicates the aggregated information to a processing system to thereby process the digital transaction.

IPC Classes  ?

• G06F 21/32 - User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints

Abstract

This document describes systems, methods, devices, and other techniques for automatically identifying and extracting medical conditions and supporting evidences from electronic health records. In some implementations, formatted text extracted from an unstructured electronic health record is obtained. The formatted text is segmented into multiple documents, wherein each document comprises a respective document type and represents a respective document encounter. Medical condition entities and supporting evidence entities referenced in each of the multiple documents are extracted. Extracted supporting evidence entities within a same document are linked to respective extracted medical condition entities from the same document using one or more of i) medical ontologies, or ii) a medical knowledge base. Output data representing linked supporting evidence entities and medical condition entities within a same document is provided.

IPC Classes  ?

• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records

Abstract

A device may receive information that identifies code associated with an application. The device may generate a technical description of the code based on the information that identifies the code associated with the application. The device may generate a set of rules based on the technical description of the code. The set of rules being associated with a semantics of business vocabulary and business rules (SBVR) format. The device may generate a set of microservices based on the set of rules. The device may provide information that identifies the set of microservices to cause an action to be performed.

IPC Classes  ?

• G06F 8/76 - Adapting program code to run in a different environment; Porting
• G06F 8/75 - Structural analysis for program understanding

Abstract

A narrative response generator receives a user data query specifying variables and data sources from which to extract information desired by a user. The narrative response presents the information desired by the user in a non-textual format such as graphs and a textual format such as one or more paraphrases that are automatically generated by a sentence struct model. The sentence struct model generates context free grammar (CFG) which provides templates for generating word sequences that contain natural language words and placeholders. The placeholders are replaced with values obtained from the user data query for generating grammatically- accurate, complete paraphrases. The narrative response may additionally include information extracted from external data sources.

IPC Classes  ?

• G06F 16/903 - Querying
• G06F 16/9038 - Presentation of query results

Abstract

It is difficult to develop, design, and/or engineer application software for applications. Systems and methods are described herein which provide application engineering platforms (AEPs). Systems and methods described herein may receive inputs associated with developing an application, determining features to be included based on the input, selecting APIs from a repository, selecting user interfaces (UIs) based on the APIs, and performing actions associated with developing the application.

IPC Classes  ?

• G06F 8/00 - Arrangements for software engineering

Abstract

Methods, systems, and apparatus for training a machine learning model to route received computational tasks in a system including at least one quantum computing resource. In one aspect, a method includes obtaining a first set of data, the first set of data comprising data representing multiple computational tasks previously performed by the system; obtaining input data for the multiple computational tasks previously performed by the system, comprising data representing a type of computing resource the task was routed to; obtaining a second set of data, the second set of data comprising data representing properties associated with using the one or more quantum computing resources to solve the multiple computational tasks; and training the machine learning model to route received data representing a computational task to be performed using the (i) first set of data, (ii) input data, and (iii) second set of data.

IPC Classes  ?

• G06N 20/00 - Machine learning

Abstract

A device may receive a plurality of data objects from a plurality of sources; identify text data, image data, and location data of the plurality of data objects; identify relevant data objects, of the plurality of data objects, based on the text data, and/or based on the image data, based on the location data, and/or based on comparing the text data, the image data, and the location data to a predefined element that identities values relevant to a particular group or subject area; assign scores to the relevant data objects based on the text data, the image data, and the location data; aggregate the scores, as one or more aggregated scores, with regard to one or more users associated with the relevant data objects; and/or perform one or more actions based on the one or more aggregated scores associated with the one or more users.

IPC Classes  ?

• H04L 12/16 - Arrangements for providing special services to substations

Abstract

Methods, systems, and apparatus for solving optimization tasks. In one aspect, a method includes receiving input data comprising (i) data specifying an optimization task to be solved, and (ii) data specifying task objectives for solving the optimization task, comprising one or more local task objectives and one or more global task objectives; processing the received input data to obtain one or more initial solutions to the optimization task based on the local task objectives, wherein at least one initial solution is obtained from a first quantum computing resource; and processing the generated one or more initial solutions using a second quantum computing resource to generate a global solution to the optimization task based on the global task objectives.

IPC Classes  ?

• G06N 20/00 - Machine learning
• G06F 17/10 - Complex mathematical operations

Abstract

Hardware acceleration supports complex software processes. In particular, a hardware security module provides encryption support for transaction chains. In one implementation, the security module circuitry provides high-speed security features and acceleration of the security features for blockchain processing.

IPC Classes  ?

• G06F 21/00 - Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
• G06F 21/71 - Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer to assure secure computing or processing of information

Abstract

Cloud Connected automated testing (CCAT) provides a low-cost, high-throughput, automated multi-thread testing platform for testing application with multiple test cases in a variety of operating environments. The platform may be hosted on cloud infrastructure. Unlike other test automation platforms, inputs to CCAT are based on human readable formats, such as keyword entries in a spreadsheet. CCAT thereby reduces the need for testers to understand highly specialized and difficult to use coding languages such as Java or Python.

IPC Classes  ?

• G06F 11/36 - Preventing errors by testing or debugging of software

Abstract

A method for assessing and improving a presence and perception of an entity includes, for one or more presence categories of data sources, determining a number of data sources in a presence category on which the entity has a presence to thereby determine a presence score for the entity. The presence score increases as the number of data sources upon which the entity has a presence increases. For each of a plurality of comments posted on one or more social media sources, the method also includes determining a perception category and sentiment score associated with each comment that is related to the entity to thereby determine a perception score for the entity. A higher perception score indicates that, on average, users have a higher perception of the entity. The method also includes generating a recommendation for improving one or more of the presence score and perception score of the entity based on the determined presence score and the determined perception score.

IPC Classes  ?

• G16Z 99/00 - Subject matter not provided for in other main groups of this subclass

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for observing, evaluating, and improving performance of one or more communication networks. A generated performance index for a communication network is received, an external performance index for the communication network is received, and in response to determining a discrepancy between the generated performance index and the external performance index, key performance indicators associated with the communication network are evaluated. The performance index is generated based at least in part on a set of key performance indicators and corresponding thresholds values. The external performance index represents user experience with the communication network. In response to determining that a value of a given key performance indicator fails a threshold comparison against its one or more corresponding threshold values, one or more settings for the communication network are automatically modified.

IPC Classes  ?

• H04L 41/08 - Configuration management of networks or network elements
• H04W 24/02 - Arrangements for optimising operational condition
• H04L 41/14 - Network analysis or design
• H04L 41/5067 - Customer-centric QoS measurements
• H04L 43/08 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
• H04L 43/0876 - Network utilisation, e.g. volume of load or congestion level
• H04L 43/16 - Threshold monitoring
• H04L 43/028 - Capturing of monitoring data by filtering

Abstract

A device may communicate with a first server to obtain first information regarding a plurality of groups of entities. The device may process the first information to generate a data model relating to attributes of the plurality of groups of entities. The device may communicate with a second server to obtain second information regarding a particular group of entities. The device may process the second information using the data model to identify a set of recommendations relating to the particular group of entities. The device may select a particular recommendation, of the set of recommendations, based on a corresponding score of the set of scores. The device may generate a user interface including the particular recommendation based on selecting the particular recommendation. The device may communicate with a plurality of client devices to cause the particular recommendation to be provided for display.

IPC Classes  ?

• G06Q 10/105 - Human resources
• H04L 67/55 - Push-based network services

Abstract

Computerized methods and systems, including computer programs encoded on a computer storage medium, may adaptively allocate resources within an enterprise. For example, a computing system may obtain data identifying an element of work. The computing system may assign the work element to a work category, establish a priority for resolving the work element within the assigned work category, and dynamically allocate the prioritized work element to an agent of the enterprise having availability to resolve the work element and having skill sets consistent with the work element. The computing system may also monitor the agent's performance while the agent applies or implements resolution processes via a corresponding agent system, and to provide, in real-time, data that characterizes the agent's performance in terms of key performance indicators to systems of the agent and other individuals across the enterprise.

IPC Classes  ?

• G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
• G06N 20/00 - Machine learning

Abstract

A device may include one or more processors. The device may obtain a first code set and a second code set. The first code set may have at least one difference from the second code set. The at least one difference may relate to addition, removal, or modification of code of the first code set in comparison to code of the second code set. The device may identify one or more first portions of the first code set and one or more second portions of the second code set. The device may concurrently compare the one or more first portions and the one or more corresponding second portions to identify the at least one difference. The device may generate comparison information identifying the at least one difference. The device may store or provide the comparison information.

IPC Classes  ?

• G06F 8/70 - Software maintenance or management

Abstract

An intelligent automatic license plate recognition (IALPR) system implements technical solutions that improve the accuracy of automatic license plate recognition. The IALPR analyzes an image of a vehicle proximate to a toll collection point using optical character recognition (OCR), and determines candidate license plate identifications based, at least in part, on the corresponding OCR confidence level. The IALPR can also perform fingerprinting for candidate license plate images and matching analysis with a knowledge base, resulting in additional confidence levels. The IALPR can also perform behavioral analysis on the candidate license plate identifications, including trip context analysis, historical behavioral analysis, or other analytics. The IALPR can generate an overall confidence level for the candidate license plate identifications responsive to the OCR and vehicle fingerprint confidence levels and the behavioral analysis. This enhanced analysis helps the IALPR reduce the number of incorrect license plate identifications and reduce the need for human review.

IPC Classes  ?

• G08G 1/017 - Detecting movement of traffic to be counted or controlled identifying vehicles
• G07B 15/06 - Arrangements for road pricing or congestion charging of vehicles or vehicle users, e.g. automatic toll systems
• G09F 7/00 - Signs, name or number plates, letters, numerals, or symbols; Panels or boards

Abstract

A device may receive, from a beacon device, a first message including a first identifier. The first identifier may be associated with the beacon device. The device may receive, from a user device, a second message including a second identifier. The second identifier may be associated with the user device. The device may determine the second identifier based on the second message and the first identifier. The device may determine an event associated with the second identifier based on the first identifier. The device may provide, to another device, information that identifies the second identifier and the event to permit the other device to identify a displacement trajectory associated with the user device.

IPC Classes  ?

• G01S 5/00 - Position-fixing by co-ordinating two or more direction or position-line determinations; Position-fixing by co-ordinating two or more distance determinations
• H04W 64/00 - Locating users or terminals for network management purposes, e.g. mobility management
• G01S 11/00 - Systems for determining distance or velocity not using reflection or reradiation

Abstract

The global proliferation of high speed communication networks has created unprecedented opportunities for geographically distributed resource identification, evaluation, selection, and allocation. However, while the opportunities exist and continue to grow, the realization of those opportunities has fallen behind. A dynamic resource assessment system helps to solve the enormous technical challenges of finding the resources, evaluating the resources, and determining how to allocate the resources to achieve the highest likelihood of successfully completing the task.

IPC Classes  ?

• G06Q 10/0639 - Performance analysis of employees; Performance analysis of enterprise or organisation operations
• G06F 17/10 - Complex mathematical operations

Abstract

A device may obtain sensor data regarding the vending device. The device may transmit the sensor data via a network connection for processing by a server. The server may store a data model. The server may be associated with identifying a response action associated with altering a configuration of the vending device. The device may receive information identifying the response action based on transmitting the sensor data via the network connection. The device may cause the response action to be performed based on receiving the information identifying the response action. The response action may be associated with altering a status of a component of the vending device. The device may provide information associated with identifying the status of the component.

IPC Classes  ?

• G07F 9/02 - Devices for alarm or indication, e.g. when empty; Advertising arrangements in coin-freed apparatus
• G01K 15/00 - Testing or calibrating of thermometers

Abstract

Data conversion circuitry receives structured records including normalized data and performs a data conversion process on the structured records to generate unstructured records including unstructured syntax. The data conversion circuitry performs the data conversion process according to an unstructured syntax requirement including a syntax field mapping between the structured records and the generated unstructured records.

IPC Classes  ?

• G06F 16/25 - Integrating or interfacing systems involving database management systems
• G06F 5/00 - Methods or arrangements for data conversion without changing the order or content of the data handled

Abstract

A development platform system is disclosed that provides a development platform configured to create new and modified web-based applications. The development platform may be configured to search for and select a design layout template from available design layout templates stored on a database library. The development platform may further be configured to search for and select a data visualization template from available data visualization templates stored on a database library. The development platform may further be configured to generate a data visualization modification interface and accept a client device customization input to modify attributes of a data visualization. Templates that are modified by the development platform may be stored for subsequent look-up on a database library according to metadata describing attributes of the templates.

IPC Classes  ?

• G06F 8/34 - Graphical or visual programming
• G06F 8/20 - Software design
• G06F 8/35 - Creation or generation of source code model driven
• G06F 16/00 - Information retrieval; Database structures therefor; File system structures therefor
• G06F 3/14 - Digital output to display device

Abstract

A device may receive information associated with an application to be tested. The device may identify test data associated with the application to be tested based on the received information. The device may associate the test data with a plurality of test cases. The device may associate the plurality of test cases with a test set. The device may associate the test set with a release. The device may provide the plurality of test cases and the test data, associated with the release, to the application to be tested. The device may receive a plurality of first results, and may compare the plurality of first results and a plurality of second results. The device may provide information for display based on comparing the plurality of first results and the plurality of second results.

IPC Classes  ?

• G06F 11/36 - Preventing errors by testing or debugging of software
• G06F 9/44 - Arrangements for executing specific programs

Abstract

A commodity-measuring device for autonomously selecting a commodity supplier among a plurality of commodity suppliers being specified within a blockchain distributed database is provided. The device comprises a microcontroller unit; a communication module configured to communicate with a network, wherein a communication from the communication module is associated with an identifier of the commodity- measuring device; a storage; and a transaction manager; wherein the microcontroller unit is configured to provide commodity consumption data to the transaction manager; the storage is configured to store a private key; the communication module is configured to retrieve a commodity supplier file stored in the blockchain distributed database, wherein the commodity supplier file includes parameters of a commodity supplier and a program; the transaction manager is configured to determine autonomously, based on the commodity consumption data and the parameters in the commodity supplier file, whether to select the commodity supplier; and if the determination is positive, the transaction manager is configured to, using the private key, send a transaction to the blockchain distributed database calling a function in the program to associate the commodity supplier file with the identifier.

IPC Classes  ?

• G06Q 50/06 - Electricity, gas or water supply

Abstract

A system for managing the operation of different components within a cloud system to accomplish various tasks, including the implementation of build features within the cloud system to achieve specific operational goals. The system may include a data defined infrastructure (DDI) tool installed within a data defined infrastructure (DDI) to manage certain features or tasks within the cloud system. The DDI may include an environment configuration database (ECDB), an orchestration engine, an automation engine, and/or other hardware and software components within the cloud system, such that the DDI tool installed on the DDI infrastructure may control operation of the ECDB, the orchestration engine, the automation engine, or other hardware and software components within the cloud system based on a set of data that fully describes the operational goal

Abstract

Scalable architectures provide resiliency and redundancy and are suitable for cloud deployment. The architectures support extreme data throughput requirements. In one implementation, the architectures provide a serving layer and an extremely high speed processing lane. With these and other features, the architectures support complex analytics, visualization, rule engines, and centralized pipeline configuration.

IPC Classes  ?

• G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
• G06F 9/38 - Concurrent instruction execution, e.g. pipeline, look ahead

Abstract

Systems, methods, and apparatus, including computer programs encoded on computer storage media, for obtaining, processing, and presenting data related to security events, and for implementing courses of action to protect assets in response to the security events. An event management module identifies malicious activity present on a first network domain and/or a second network domain based on received network domain activity. A threat intelligence module receives data identifying the malicious activity in first data constructs of a predefined data structure. The threat intelligence module obtains additional data related to the identified malicious activity and generates second data constructs that include enriched data regarding the malicious activity. The enriched data includes data describing a campaign in which at least a portion of the malicious activity is involved and one or more courses of action. A course of action module receives the second data constructs and implements a given course of action.

IPC Classes  ?

• H04L 41/0631 - Management of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis

Abstract

Systems, methods, and apparatus, including computer programs encoded on computer storage media, for obtaining, processing, and presenting data related to security events, and for implementing courses of action to protect assets in response to the security events. An event management module identifies malicious activity present on a first network domain and/or a second network domain based on received network domain activity. A threat intelligence module receives data identifying the malicious activity in first data constructs of a predefined data structure. The threat intelligence module obtains additional data related to the identified malicious activity and generates second data constructs that include enriched data regarding the malicious activity. The enriched data includes data describing a campaign in which at least a portion of the malicious activity is involved and one or more courses of action. A course of action module receives the second data constructs and implements a given course of action.

IPC Classes  ?

• H04L 12/22 - Arrangements for preventing the taking of data from a data transmission channel without authorisation

Abstract

A device may obtain text to be processed to extract constraints corresponding to an object in the text. The constraints may define values permitted to be associated with the object. The device may extract the constraints based on identifying patterns in the text. The device may generate, based on the constraints, positive test data and negative test data for testing values for the object. The positive test data may include a first value that satisfies each of the constraints, and the negative test data may include a second value that violates at least one of the constraints. The device may provide information that identifies the positive test data and the negative test data.

IPC Classes  ?

• G06F 40/20 - Natural language analysis
• G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
• G06F 11/36 - Preventing errors by testing or debugging of software

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for predictive modeling for adjusting initial values are disclosed. In one aspect, a method includes the actions of accessing transaction history data that indicates one or more transaction details associated with the transaction, a predicted value, and a final value. The actions further include determining a difference value between the predicted value and the final value. The actions further include generating a predictive model that is trained to estimate. The actions further include receiving one or more transaction details and a predicted value associated with a subsequently received transaction. The actions further include providing the one or more transaction details as input to the predictive model. The actions further include receiving an adjustment value to apply to the predicted value. The actions further include providing, for output, data indicating the adjustment value.

IPC Classes  ?

• G06Q 40/04 - Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

A device may receive lifestyle information corresponding to an individual with a medical condition. The device may create a lifestyle timeline, associated with the individual, that includes a plurality of items of lifestyle information, included in the lifestyle information, arranged in a chronological order. The device may generate, based on the lifestyle timeline, a recommendation or a prediction associated with a metric related to the medical condition. The recommendation may be generated based on one or more of the plurality of items of lifestyle information. The prediction may be generated using a prediction model that uses one or more of the plurality of items of lifestyle information as input, and generates the prediction using the prediction model. The device may provide information associated with the recommendation or the prediction to identify a dosage associated with treating or managing the medical condition

IPC Classes  ?

• G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• G16H 20/13 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
• G16H 20/17 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered via infusion or injection
• G16H 20/30 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• G16H 20/60 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
• G16H 20/70 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
• A61J 7/04 - Arrangements for time indication or reminder for taking medicine, e.g. programmed dispensers

Abstract

According to examples, intelligent visualization munging may include transforming and enriching data that is to be visualized, determining features of the transformed and enriched data, determining a user role of a user associated with the transformed and enriched data, and a user interaction of the user. Intelligent visualization munging may further include learning a behavior of the user, and analyzing the features, the user role, the user interaction, and a learned behavior model to generate a recommendation that includes a predetermined number of visualizations from a plurality of available visualizations to display the transformed and enriched data. The predetermined number of visualizations is less than the plurality of available visualizations.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06N 20/00 - Machine learning
• G06F 3/14 - Digital output to display device
• G06F 5/00 - Methods or arrangements for data conversion without changing the order or content of the data handled

Abstract

According to examples, intelligent data munging may include ascertaining data that is to be transformed, and determining, based on an analysis of the ascertained data, a sample of the ascertained data. Intelligent data munging may further include enriching the sample of the ascertained data, determining features of the enriched sample of the ascertained data, and determining, based on the features, a transformation to be applied to the enriched sample of the ascertained data to transform the enriched sample of the ascertained data from a first format to a second format. Further, intelligent data munging may include validating the determined transformation, and generating, based on the validation of the determined transformation, a script that is to be applied to the ascertained data to transform the ascertained data from the first format to the second format.

IPC Classes  ?

• G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
• G06N 20/00 - Machine learning
• G06F 5/00 - Methods or arrangements for data conversion without changing the order or content of the data handled

Abstract

A method for decommissioning an application operating on a computer system or a computer system includes receiving, at a decommissioning system, information that specifies a server to analyze. The decommissioning system determines one or more applications operating on the server, one or more instruction code libraries that are being utilized by the one or more applications, and hardware dependencies of the one or more instruction code libraries. Based on the determined hardware dependencies, the decommissioning system determines whether the application is suitable for migration to a cloud computing system. The decommissioning system generates a report indicating a suitability for migration of the application to the cloud computer system.

IPC Classes  ?

• H04L 41/0823 - Configuration setting characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability
• G06F 8/60 - Software deployment
• H04L 41/0826 - Configuration setting characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability for reduction of network costs
• H04L 43/065 - Generation of reports related to network devices
• G06Q 10/20 - Administration of product repair or maintenance

Abstract

A device may receive a text, from a text source, in association with a request to generate an ontology for the text. The device may generate a set of word vectors from a list of terms determined from the text. The device may determine a quantity of term clusters to be generated to form the ontology based on the set of word vectors. The device may generate term clusters based on the quantity of term clusters, attributes, and/or non-hierarchical relationships. The term clusters may be associated with concepts of the ontology. The device may provide the term clusters for display via a user interface associated with a device.

IPC Classes  ?

• G06F 16/36 - Creation of semantic tools, e.g. ontology or thesauri
• G06F 40/30 - Semantic analysis

Abstract

A method and a system control the water production for a water distribution network. The method includes collecting field sensor data from a water distribution network, using the received data to model the water distribution network and determining an optimal water flow, and generating the optimal water production plan for controlling the water production in the water distribution network based on received data including the sensor data and the historical data. The system includes a process and memory and processor executable instructions to carry out the above method.

IPC Classes  ?

• G05B 17/02 - Systems involving the use of models or simulators of said systems electric
• E03B 7/00 - Water main or service pipe systems
• G05B 19/042 - Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors

Abstract

The invention relates to a housing having a housing wall (1) comprising a polymer including electrically conductive particles, wherein an inner chamber (6) is provided in the housing, and is formed and enclosed by the housing wall (1) and into which a mobile telephone (12) can be inserted, and the housing wall (1) is designed to attenuate a mobile radio signal of the mobile telephone (12) by >= 3 dB, as compared to unobstructed propagation, on the side of the housing wall (1) facing away from the inner chamber (6).

IPC Classes  ?

• H01Q 17/00 - Devices for absorbing waves radiated from an antenna; Combinations of such devices with active antenna elements or systems
• H04W 24/08 - Testing using real traffic
• H04B 1/3877 - Arrangements for enabling portable transceivers to be used in a fixed position, e.g. cradles or boosters
• H04B 17/18 - Monitoring during normal operation

Abstract

The present application provides a user configurable test system for set-top boxes (STB) and other consumer devices providing video output. In particular, it provides for a method of improving an Optical Character Recognition (OCR) process in such test systems.

IPC Classes  ?

• H04N 17/00 - Diagnosis, testing or measuring for television systems or their details

Abstract

The present application relates to set top boxes and relates to the inclusion of a diagnostic function in the set top box which may be activated remotely or respond internally to the detection of faults or changes in status. The diagnostic function may emulate key presses from an infrared remote control to perform a test.

IPC Classes  ?

• H04N 5/44 - Receiver circuitry
• H04N 21/65 - Transmission of management data between client and server

Abstract

The present application is directed to a test system for testing set-top boxes which provide a video output to a television. The test system records the execution of a test script, inputs to the set-top box and video output, each separately with a time stamp. The test system has a graphical user interface for playing back the video, inputs and scripts in a synchronised fashion.

IPC Classes  ?

• H04N 17/00 - Diagnosis, testing or measuring for television systems or their details