41 results about "Machine-readable data" patented technology

Systems and methods disclosed herein perform privacy-preserving evaluations of artificial intelligence (AI) agents. A first AI agent associated with a first entity obtains a machine-readable data structure defining one or more operative boundaries for a second AI agent associated with a second entity. The system generates a unique fixed reference value representing the machine-readable data structure by applying a first transformation operation set, and transmits the unique fixed reference value to a multi-agent storage to store the value. The system receives, via the multi-agent storage, a verification artifact from the second AI agent that indicates an observed value based on internal operational data of the second AI agent corresponding to the operative boundaries. The first AI agent determines a verification status of the verification artifact by comparing the unique fixed reference value with the observed value, and autonomously generates a verification record including a representation of the verification status.

Systems and methods disclosed herein perform privacy-preserving evaluations of artificial intelligence (AI) agents. A first AI agent associated with a first entity obtains a machine-readable data structure defining one or more operative boundaries for a second AI agent associated with a second entity. The system generates a unique fixed reference value representing the machine-readable data structure by applying a first transformation operation set, and transmits the unique fixed reference value to a multi-agent storage to store the value. The system receives, via the multi-agent storage, a verification artifact from the second AI agent that indicates an observed value based on internal operational data of the second AI agent corresponding to the operative boundaries. The first AI agent determines a verification status of the verification artifact by comparing the unique fixed reference value with the observed value, and autonomously generates a verification record including a representation of the verification status.

The present invention provides a method and system for automatically and seamlessly processing clinical trial source data into electronic data capture (EDC) systems. In one embodiment, a file structure is defined for an electronic binder system (eBinder); source data is uploaded to the eBinder; the source data is encrypted, Patient Identifiable Information in the source data is masked; the source data is converted into machine readable plain text in the JavaScript Object Notation (JSON) format using Natural Language Processing (NPL) technologies; the JSON data is converted into tabulated machine readable data in the HyperText Markup Language (HTML) format using NPL technologies; the HTML data is converted into machine understandable data using NPL technologies; the machine understandable data is populated into EDC datasets using NPL technologies; the source data and converted data are displayed side-by-side for source data verification; and a platform is provided for regulatory data verification or auditing.

A method comprises receiving at least one data record associated with a patient, the data record including one or more data items represented as image data. Then, the method comprises pre-processing the at least one data record to enhance legibility of at least one data item of the one or more data items of the at least one data record. Then, the method comprises, using at least a first machine learning model, converting at least a portion of the pre-processed at least one data record into at least one machine-readable data record. Then, the method comprises identifying a standardized format. Then, the method comprises converting the machine-readable data record to the standardized record format and using at least a second machine learning model and assigning one or more predetermined activity codes to the at least one machine-readable data record in the standardized record format.

The invention discloses an information fusion and reasoning method and system based on multi-agent collaborative networking search, and relates to the technical field of network information, and the method comprises the steps: a deep research strategy scheduling agent deconstructs an unstructured request through a task formalization mechanism, generates a high-dimensional instruction code, and dynamically optimizes an execution path. And the network intelligence index generation agent extracts and screens the trusted URL by using a rule engine and a semantic evaluator based on the code, and generates a structured link instruction stream. The structured analysis intelligent agent implements multi-level semantic distillation and conversion on an original document to obtain key value pair representations, and the key value pair representations are packaged into machine readable data. And generating a comprehensive intelligence abstract with consistent logic through the information fusion analysis agent. And the natural language generation engine converts the information into a professional report, and returns the professional report to the scheduling module through a feedback interface to realize cognitive closed-loop iterative optimization. The technical problem that in the prior art, it is difficult for geologists to obtain accurate, comprehensive and credible professional conclusions is solved.

Techniques are provided for processing rules expressed in a domain-specific language. A computing system may receive a rule including an entity identifier, a property of the entity, and one or more logical operators delimited by syntactic tokens of the language. The rule is parsed into an abstract syntax tree (AST) representation that structurally represents entities, properties, and conditional logic, and the AST is transformed into an executable function configured to evaluate input data objects defined according to a machine-readable data model. Execution of the function on input data produces a logical outcome along with intermediate results corresponding to evaluations of individual conditions and logical operators. The computing system generates an execution trace comprising the logical outcome and the intermediate results, the trace being stored in a structured log retrievable to provide evidence of how outcomes were determined.

There is provided a computer implemented method in which a deep learning model detects and interprets real time events from an input data stream, in which the detected and interpreted events are output in a structured, machine-readable representation of data that conforms to a machine-readable language.

Systems and methods disclosed herein perform privacy-preserving evaluations of artificial intelligence (AI) agents. A first AI agent associated with a first entity obtains a machine-readable data structure defining one or more operative boundaries for a second AI agent associated with a second entity. The system generates a unique fixed reference value representing the machine-readable data structure by applying a first transformation operation set, and transmits the unique fixed reference value to a multi-agent storage to store the value. The system receives, via the multi-agent storage, a verification artifact from the second AI agent that indicates an observed value based on internal operational data of the second AI agent corresponding to the operative boundaries. The first AI agent determines a verification status of the verification artifact by comparing the unique fixed reference value with the observed value, and autonomously generates a verification record including a representation of the verification status.

There is provided a computer implemented method for automated analysis or use of data, comprising the steps of: (a) storing in a memory store a structured, machine-readable representation of data that conforms to a machine-readable language; in which the data includes personal health or medical data; (b) automatically processing the structured representation of the data to analyse the personal health or medical data; in which the method includes the steps of (c) the machine-readable language representing a question in a memory in the structured, machine-readable representation of data; and (d) automatically generating a response to the question, using the following steps: (i) matching the question with the structured, machine-readable representations of data previously stored in the memory store; (ii) fetching and executing one or more computation units, wherein the computation units represent computational capabilities relevant to answering the question; (iii) fetching and execution of one or more reasoning passages.

Systems, methods, and computer-readable storage media for scientific manuscript generation using large language models are disclosed. A system can include one or more processors configured to receive an input including at least one machine-readable data object divided by one or more input node identifiers, generate a multi-level resource mapping encoding associations between the input node identifiers and one or more output node identifiers, construct a set of model input parameters based on a selection of resources from the machine-readable data object, provide each set of model input parameters to a first generative model to generate an output data object, generate at least one metric for each output data object based on a comparison to a structural or coverage parameter, automatically generate modified model input parameters to regenerate the output, and generate a function that creates an annotation linking each output to at least one input node identifier.

The present invention provides a method and system for automatically and seamlessly processing clinical trial source data into electronic data capture (EDC) systems. In one embodiment, a file structure is defined for an electronic binder system (eBinder); source data is uploaded to the eBinder; the source data is encrypted, Patient Identifiable Information in the source data is masked; the source data is converted into machine readable plain text in the JavaScript Object Notation (JSON) format using Natural Language Processing (NPL) technologies; the JSON data is converted into tabulated machine readable data in the HyperText Markup Language (HTML) format using NPL technologies; the HTML data is converted into machine understandable data using NPL technologies; the machine understandable data is populated into EDC datasets using NPL technologies; the source data and converted data are displayed side-by-side for source data verification; and a platform is provided for regulatory data verification or auditing.

The proposed technical solution relates to methods for automated text processing and can be used in the generation of text corpora. The claimed invention solves the technical problem of creating a method and / or a computing device and / or a system and / or a machine-readable data carrier which overcome the disadvantages of the prior art and, in so doing, provide for the precise automated generation of a text corpus which can subsequently be used for pre-training, or training, or post-training classification models and / or clustering models.

The proposed technical solution relates to methods for automated text processing and can be used in the generation of text corpora. The claimed invention solves the technical problem of creating a method and / or a computing device and / or a system and / or a machine-readable data carrier which overcome the disadvantages of the prior art and, in so doing, provide for the precise automated generation of a text corpus which can subsequently be used for pre-training, or training, or post-training classification models and / or clustering models.

The description relates to computer-assisted generation of long-form text by creating a schema that includes a declarative and machine-readable data format. Based on the schema, processes iteratively generate suggested code to populate a specification that provides the narrative framework for the long-form text. The specification includes structure and substance for inclusion in the long-form text. The interactive nature of the specification development allows a user to progressively update and confirm automatically generated suggestions. In this manner, the specification is updated according to approved code selected from the iteratively generated code. Additional processes serialize the specification to generate multiple unit specifications. A large language model (LLM) is used to generate the long-form text based on the unit specifications.

A computer-implemented method for providing personalized feeding recommendations based on a trained model of a user's recording habits related to a dietary and an activity of a subject, obtaining visual image including handwritten data related to the dietary and the activity of the subject by using a camera of a computing device; employing a trained OCR model to scan and extract textual information from the obtained visual image, thereby converting the data in the visual image into a machine-readable data.

The invention discloses a method for determining a maximum open time (31) of a reactive material (21) during a joining process (22), which maximum open time is valid for current conditions. The method comprises providing first machine-readable data (28) which characterize batch-accurate material properties provided by the manufacturer (27). Furthermore, second digital data characterizing current parameters of the joining process (22), such as the ambient temperature, are received. The maximum open time (31) valid for the current conditions is determined by means of a mathematical-physical model, into which the first and second data are input. This enables more flexible and more robust process control compared to static worst case parameters.

The description relates to computer-assisted generation of long-form text by creating a schema that includes a declarative and machine-readable data format. Based on the schema, processes iteratively generate suggested code to populate a specification that provides the narrative framework for the long-form text. The specification includes structure and substance for inclusion in the long-form text. The interactive nature of the specification development allows a user to progressively update and confirm automatically generated suggestions. In this manner, the specification is updated according to approved code selected from the iteratively generated code. Additional processes serialize the specification to generate multiple unit specifications. A large language model (LLM) is used to generate the long-form text based on the unit specifications.

The proposed technical solution relates to methods for automated text processing and can be used in the generation of text corpora. What is proposed is a computing device for the automated processing of natural language text. The claimed invention solves the technical problem of creating a method and / or a computing device and / or a system and / or a machine-readable data carrier which overcome the disadvantages of the prior art and, in so doing, provide for the precise automated generation of a text corpus which can subsequently be used for pre-training, or training, or post-training classification models and / or clustering models.

The proposed technical solution relates to methods for automated text processing and can be used in the generation of text corpora. The claimed invention solves the technical problem of creating a method and / or a computing device and / or a system and / or a machine-readable data carrier which overcome the disadvantages of the prior art and thus provide for the precise automated generation of a text corpus which can subsequently be used for pre-training, or training, or post-training classification models and / or clustering models.

The self-propelled construction machine I according to the invention has a DGNSS rover unit 14 for receiving satellite signals from a global navigation satellite system and correction signals from a reference station 15 to be set up in the vicinity of the self-propelled construction machine. The DGNSS rover unit 14 comprises a processing and evaluation unit 18, which is configured such that, based on the satellite signals and the correction signals from the reference station, construction machine position data describing the position of a construction machine reference point R on the construction machine is determined. The processing and evaluation unit 18 is further configured such that, for a reference station position data record stored in a reference station position data memory 23, at least one machine-readable data record, in particular a QR code, is generated, which is displayed on a display 8A.The QR code can be scanned with a smartphone 26 equipped with a map service and navigation function, making it easy to locate the installation point for a reference station in the field. Alternatively, the data can also be read using an NFC receiver (NFC reader) based on RFID technology.

A self-propelled construction machine I according to the invention has a DGNSS mobile station unit 14 for receiving satellite signals of a global navigation satellite system and correction signals of a reference station 15 arranged in the vicinity of the self-propelled construction machine. The DGNSS mobile station unit 14 comprises a calculation and evaluation unit 18 configured to determine construction machine position data describing a position of a construction machine reference point R on the construction machine based on the satellite signal and the correction signal of the reference station. The calculation and evaluation unit 18 is further configured to generate at least one machine-readable dataset, in particular a QR code, for a reference station location dataset stored in the reference station location data memory device 23, the dataset being displayed on a display 8A. The QR code can be scanned through a smart phone 26 provided with a map service with a navigation function, so that a setting point for setting the reference station can be easily found on a construction site. In an alternative embodiment, data may also be scanned using an RFID technology-based NFC receiving unit (NFC reader).

The proposed technical solution relates to methods for automated text processing and can be used in the generation of text corpora. The claimed invention solves the technical problem of creating a method and / or a computing device and / or a system and / or a machine-readable data carrier which overcome the disadvantages of the prior art and, in so doing, provide for the precise automated generation of a text corpus which can subsequently be used for pre-training, or training, or post-training classification models and / or clustering models.

The present application relates to the technical field of smart city, and discloses a smart city multi-modal data acquisition and fusion method and system.The present application comprises: acquiring smart city system data;performing data cleaning on the smart city system data according to a pre-trained naive Bayes model, and extracting metadata of data items;performing data standardization according to the metadata of the data items to obtain standardized data information;performing data conversion on the standardized data information according to a pre-formed semantic mapping rule library to obtain machine-readable data;merging and compressing the machine-readable data based on principal component analysis to obtain reduced dimension readable data;performing data fusion on the reduced dimension readable data according to a pre-set fusion strategy to obtain fusion data information, and storing the fusion data information.This method converts various heterogeneous data into machine-understandable information, effectively performs data fusion, and improves the usability of data.

Described herein relates to a system and method that supports the creation and execution of collaborative intelligent agents to process machine-readable data into dynamic and / or related outputs. As such, the collaborative intelligent agent system and / or methods thereof may include a compiler to generate an executable expression tree, an executor to manage intelligent agent execution using the expression tree, and / or a processor to manage intelligent agent collaboration during execution. Additionally, using machine-readable inputs, the collaborative intelligent agent system and / or methods thereof may automatically execute the collaborative intelligent agents to dynamically induce outputs, without requiring user interaction. As such, the collaborative intelligent agent system and / or methods thereof may also be configured to realize the second pillar of the Semantic Web and / or may improve upon HTML or machine-readable code only, providing a mechanism to automatically produce dynamic outputs based on input data.

Disclosed are systems and methods that provide a novel framework for the creation, management and electronic transfer of electronic, machine-readable data as tangible digital assets accessible from a network storage (e.g., blockchain, for example), which can be utilized by entities via native and / or third party software. The disclosed framework can operate by transforming data in a raw static format to a liquid format through standardization and factorization. The data can be standardized via tags associated with governance and policy frameworks, as well as infrastructure requirements. In some embodiments, the (tagged) data can be factorized to create data (or containers, data models or collections of containers / models) as labeled, intelligent data. And, the framework can then electronically transfer the labeled data. As a result, capabilities of data liquidity can be achieved via a web-agnostic storage and framework accessible through smart contracts.

A mechanical sending unit base configured for integration with a hinge assembly, such as those used in hydraulic transom brackets like the Porta Bracket. The system can comprise a stationary component affixed to the hinge, a movable component configured to rotate in correspondence with the hinge's motion, and a converter that captures and translates this motion into digital signals. The movable component may include a protrusion received by a converter receptacle, enabling rotation about a shared central axis. The converter may include a sensor that translates arc-length movement into machine-readable data compatible with NMEA 2000 networks. The stationary component may comprise an aperture patterns for simplified, non-invasive mounting. As a result, the base enables real-time positional feedback of hinge motion without modifying existing hinge / product geometry and is suitable for marine environments due to its corrosion-resistant construction.

A computer-implemented digital knowledge management system for institutional learning and decision support, comprising the following: A user interaction interface configured to receive structured institutional information from a variety of users connected to a university. This structured institutional information includes strategic issues, institutional goals, performance indicators, academic activity data, and decision-relevant input. an input processing unit that is operationally connected to the user interaction interface and is configured to capture, classify, and convert the received structured institutional information into machine-readable data sets; a collaborative culture assessment unit consisting of at least one processor and a memory in which executable instructions are stored, wherein the collaborative culture assessment unit is configured to collect and process organizational behavior data representing loyalty, engagement, cohesion, well-being and sense of community among members of the institutional leadership; a knowledge generation unit that is operationally linked to the collaborative culture assessment unit, wherein the knowledge generation unit is configured to analyze received knowledge records and generate new institutional knowledge by exploring alternative ideas, identifying new insights, and combining individual and collective institutional contributions; a knowledge exchange unit that is communicatively linked to the knowledge generation unit, wherein the knowledge exchange unit is configured to distribute the generated institutional knowledge to authorized users via controlled communication channels and structured knowledge dissemination procedures; a knowledge application unit designed to transform distributed institutional knowledge into decision support tools, including proposed strategic actions, operational recommendations, and measurable performance targets; an institutional learning repository consisting of a permanent digital storage system configured to store knowledge records, decision outcomes, institutional experiences, and insights gained from implemented decisions; a decision quality assessment processor that is operationally linked to the institutional learning repository and the knowledge application unit and is configured to evaluate generated decisions against predefined institutional criteria, including problem-solving effectiveness, strategic value contribution, achievement of institutional goals, and contribution to organizational learning; and a coordination processor configured to coordinate the operational interaction between the collaborative culture assessment unit, the knowledge generation unit, the knowledge sharing unit, the knowledge application unit, the institutional learning repository, and the decision quality assessment processor, such that the collaborative organizational conditions influence knowledge generation, knowledge distribution, knowledge utilization, and the subsequent evaluation of strategic decisions.

The proposed technical solution relates to methods of automated text processing and can be used in the generating of text corpuses. The technical problem solved by the claimed invention is the creation of a method and / or a computer device and / or a system and / or a machine-readable data carrier that do not have the disadvantages of analogs and thus ensure accurate automated generation of a text corpus, which can subsequently be used for pre-training, or training, or additional training of classification models and / or clustering models.

The proposed technical solution relates to methods for automated text processing and can be used in the generation of text corpora. The claimed invention solves the technical problem of creating a method and / or a computing device and / or a system and / or a machine-readable data carrier which overcome the disadvantages of the prior art and, in so doing, provide for the precise automated generation of a text corpus which can subsequently be used for pre-training, or training, or post-training classification models and / or clustering models.

In order to determine an update sequence for updating machine-readable data processed by devices (41-46) communicatively coupled to a monitoring and data acquisition system (60), the monitoring and data acquisition system (60) operates to communicatively interface with a fleet management system (80).