448 results about "Input field" patented technology

Implementations relate to processing an image of a machine-read-able identifier (e.g., a QR code or other 2D barcode) to extract information that is encoded in the machine-readable identifier, and using the extracted information in automatically populating input fields of a fillable form that is being rendered at an application (e.g., a web browser application) of a computing device. Some implementations convert certain information, extracted from a machine-readable identifier, to a converted format and cause the converted format information to be populated in a corresponding input field in lieu of the certain information in its raw format that is extracted from the machine-readable identifier.

The invention belongs to the technical field of data processing, and particularly relates to a potential safety hazard real-time identification method and system based on a multi-modal large model, the system comprises the multi-modal large model, a field knowledge base and a multi-modal inference engine, the multi-modal large model is responsible for visual feature extraction and scene semantic understanding of an input field image, and the field knowledge base is responsible for field knowledge base analysis; processing a natural language query provided by a user; the domain knowledge base stores construction safety related laws and regulations, guidelines and historical cases, and factual basis is provided for the system through a structured storage and efficient retrieval mechanism; the multi-modal reasoning engine coordinates the whole process of visual understanding, task decomposition, knowledge retrieval and report generation, and is a core control module for realizing multi-modal reasoning and decision making. And refined understanding of entities and hidden dangers in a construction scene is realized. According to the system and the method thereof, the image content and the text specification can be dynamically fused, and missing detection or misjudgment caused by modal splitting in a traditional method is avoided.

The invention relates to the technical field of image enhancement, in particular to a field-level crop image enhancement system based on multi-source remote sensing data, and the system comprises an artifact joint detection module which analyzes the mutation or periodicity of a statistical mean value and a variance value in the row and column directions of an input field-level remote sensing image, and recognizes an artifact stripe region. According to the invention, the method achieves the high-precision removal of thin clouds and stripe artifacts through carrying out the mutability analysis of the local mean and variance of the input remote sensing image in the row and column directions, positioning a stripe artifact region, and building an attenuation numerical relationship in combination with the spectral information of an adjacent clear sky reference region, and reduces the ground feature information loss in the image. Multi-scale coefficient decomposition is further performed on the image after artifact removal, texture features are extracted from homogeneous crop canopies in adjacent undamaged areas, and high-frequency coefficients of damaged areas are dynamically replaced and reconstructed, so that the texture structures of the damaged areas are highly consistent with those of the adjacent areas, and the regional texture continuity and authenticity are improved.

The invention discloses an oil reservoir production dynamic prediction method fusing discrete gradient information, and belongs to the technical field of oil reservoir development and artificial intelligence crossing, and the method comprises the steps: building a heterogeneous oil reservoir oil-water two-phase flow numerical simulation data set based on a numerical simulation method; designing a double-branch network structure and extracting spatial and physical characteristics of input field data in parallel, wherein the spatial and physical characteristics comprise a main characteristic coding branch and a differential operator branch; designing a backbone network to carry out deep nonlinear modeling; an efficient pressure and saturation field prediction neural network model is constructed based on a double-branch network structure and a backbone network, in a model training stage, spatial region observation points of part of time steps are used to participate in data item loss calculation, and meanwhile, physical control equation residuals are introduced into all time steps and a whole space to serve as physical loss items; a trained efficient pressure and saturation field prediction neural network model is obtained, and high-precision prediction of a full-time-sequence pressure field and a saturation field is achieved.

A multi-channel ticket creation and service management system that includes: a graphical interface controller configured to provide a graphical user interface (GUI) accessible through a plurality of predefined Uniform Resource Locators (URLs), the GUI including interactive service request forms associated with a plurality of hierarchical service and subservice classifications; a form processing circuit operatively coupled to the graphical interface controller and configured to receive a selected service-subservice combination from a user and dynamically populate subsequent input fields based on a predefined service taxonomy, the input fields including contact information, email address, subject, location identifier, area of ​​responsibility field, and a description field; a rule execution logical processing unit coupled to the form processing circuitry, the rule execution logical processing unit configured to enable or disable one or more context-sensitive fields based on logical rules stored in a service-subservice dependency tree, the logical rules governing the enablement of date and time fields exclusively when the selected service is journalism and the selected subservice is newspaper reporting; an authentication mapping processor comprising a session parser and a user-to-department resolver, wherein the session parser is configured to extract user credentials and associated metadata from session cookies or authentication tokens, and the user-to-department resolver is configured to auto-populate an activity-driven scope field based on the extracted metadata and an organizational mapping scheme; and a validation and transmission control unit configured to check the completeness and data type conformity of all enabled fields, generate a structured ticket record, and transmit it to a central ticket management platform.

Systems and methods for custom filtering of large language model content are provided. A request associated with a user device may be received at a platform associated with a secure network environment. The request may concern usage of an online service associated with a large language model (LLM). A user interface may be generated that includes an input field. Prompt data may be provided by the user device via the input field of the user interface. The prompt data may be determined to include sensitive data in accordance with a data model trained to recognize patterns associated with sensitive data. The received prompt data may be modified to remove the sensitive data. The modified prompt data may be routed over a communication network to the online service associated with the LLM.

Contextual user information is obtained including information descriptive of users, and / or information provided by the users to an existing input field. Based on the contextual user information, a data object of a plurality of data objects is selected. The data object is indicative of one or more input fields of a dynamically rendered form. The data object includes information indicative of a field type for each of the one or more input fields. Rendering information is sent to a user computing device associated with a user of the users. The rendering information includes the data object and instructions to render the dynamically rendered form from the data object.

A method is provided. The method is executed by a transformation engine implemented as a computer program within a computing environment. The method includes selecting a transformation option to transform source data of a source field and providing an input field that prompts for an input. The source data is in a first format. The method includes transforming the source data into transformed data based on the transformation option and the input and providing the transformed data to a destination field. The transformed data is in a second format.

One or more data objects from at least one of HR data system may each contain data fields storing HR information. A graphical user interface (GUI) may present primitive coding blocks representing standard graphic programming functions and custom business blocks representing high-level operations customly directed to the one or more data objects. A visual workflow may be constructed using at least one block selected, by a user of the GUI, wherein the at least one block represents operations linking the data fields of the one or more data objects to corresponding input fields of the at least one block. The at least one block of the visual workflow may be translated into a custom data connector comprising executable instructions for obtaining values for the corresponding input fields from the linked data fields and generating, based on the values, at least one corresponding data object storing the HR information.

A computer-implemented method for managing network services for a cellular network provider comprising providing at least one search input field and a subscriber identifier selection field and receiving a user selection of an IMSI identifier type and a query input of an IMSI number. Based on the user selection of the IMSI identifier type, querying a PGW using the IMSI number. In response to querying the PGW, receiving a first set of subscriber information associated with the subscriber including an MSISDN number associated with the subscriber. In response to receiving the MSISDN number, querying at least one additional system using the MSISDN number. In response to querying the at least one additional system using the MSISDN number, receiving a second set of subscriber information associated with the subscriber, and populating one or more fields of a GUI with the first and second set of subscriber information.

An autonomous fraud / AML reporting system and methods are provided that are configured to automate SAR narrative generations using prompts to a generative AI service by an automated SAR narrative system. The system includes a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform narrative generation operations which include receiving a SAR, loading a prompt template that is associated with generating a SAR narrative by the generative AI service, extracting SAR data corresponding to one or more of prompt input fields for the prompt template, creating an updated prompt based on the extracted SAR data and the prompt template, calling the generative AI service using the updated prompt, receiving a response to the updated prompt, combining the responses and generating and storing the SAR narrative.

Some embodiments automatically identify a target of a robotic process automation (RPA) activity (e.g., a button to click, an input field to fill out) according to a semantic similarity between a design-time label of the target and a label of a target candidate selected from a runtime instance of the target UI. Semantic similarity herein denotes likeness of meaning, as opposed to wording. Some embodiments employ a language model (LM) to quantify semantic similarity.

Methods, storage systems and computer program products implement embodiments of the present invention method for protecting a client computer, which includes a processor and a display. The method includes analyzing a web page that was downloaded to the client computer, and identifying, by the processor, a password input field in the web page. After rendering the password input field to the display, an input to the password input field is captured, and the captured input is evaluated against a specified password policy. Finally, an alert is generated upon detecting a violation of the specified password policy.

A system including an artificial intelligence (AI) engine and an AI-based method are provided for dynamically predicting and suggesting emojis on a quick access emoji interface. The AI engine detects an input message in an input field on a graphical user interface of a user application. The AI engine processes the input message to identify elements, for example, character elements, image elements, patterns, etc., of the input message. The AI engine analyzes and determines a context and factors, for example, emoji positions, one or more languages, intent, user and global preferences, etc., associated with the input message for each element of the input message. The AI engine dynamically generates predictions of emojis based on the context and one or more factors in real time. The AI engine renders one or more grouped sets of emojis on the emoji interface based on the dynamically generated predictions.

This invention pertains to a golf guidebook, either physical or electronic, that incorporates golf-related data specific to a selected golf course. The data is computationally derived from sensor information, captured by an unmanned aerial vehicle flown above the course. The guidebook provides high-resolution imagery, distance mark-ups, and elevation deltas for individual golf holes. It may also feature putting-green maps with contour lines, interactive user-input fields, and synchronization capabilities with a mobile application for performance tracking. Additional features may include reusable or replaceable pages, environmental resistance, and an inverted color scheme for enhanced visibility in direct sunlight.

The invention discloses a general text matching form method and system based on a large language model, and relates to the technical field of natural language processing, the method comprises the following steps: obtaining and preprocessing text data of a user side, and defining an input field of a form based on the preprocessed text data; in combination with the preprocessed text data and the defined form input field, cue words are obtained, a pre-constructed large language model is used for analyzing the cue words, analysis results are obtained, and a semantic similarity algorithm is used for matching the analysis results; and outputting a matching result according to a preset format, and verifying the output result to optimize the large language model. According to the invention, through text data acquisition and preprocessing, the text processing efficiency is improved; meanwhile, the form input field is defined based on the preprocessed text data, so that the form can more accurately reflect the structure and content of the text data, the flexibility of form definition is enhanced, and the requirements of different application scenes are met.

A copy-or-generate model architecture is provided that a generates generation distribution obtained from the outputs of the last decoder layer and a copy distribution built from the cross-attention scores of the last decoder layer. The model applies copy weights to the generation distribution and copy distribution to determine whether to generate a next token or to copy a token from the prompt. The model provides better security by ensuring that the input values from the prompt are directly copied to the output when appropriate, such that the model is blind to the original values to copy. In a semi-sandboxed configuration, additional information may be input to the model to help the model adapt the output based on the context of those input fields.

The invention provides an asynchronous picture generation and analysis method and device. The problems that in the prior art, a picture generation and analysis method is low in efficiency and poor in real-time performance are solved. The method specifically comprises the following steps of S1, obtaining input field data; s2, if the field data does not comprise any one of the analysis data, the analysis data and the task-id, executing a step S3, otherwise, executing a step S4; s3, assembling picture features and request parameters according to the input field, and calling a picture generation interface to generate a picture according to the request parameters to form the picture; and S4, inputting the input field into the LLM, and performing query analysis through the LLM to form a query analysis result.

The embodiment of the invention provides a product production plan data processing method and device, a medium and electronic equipment. The method comprises the following steps: acquiring a pre-created target production plan model in which an input field of product production basic data and an output field of product production plan data are defined; a target production plan strategy comprising at least one model constraint and at least one model target is configured in the target production plan model, each model constraint is provided with a priority used for limiting the priority degree that each model constraint is met, each model target is provided with a priority used for limiting the priority degree that each model constraint is met, and each model target is provided with a priority used for limiting the priority degree that each model constraint is met; the priority limiting module is used for limiting the priority degree that each model target is met; and inputting the product production basic data limited by the input field into the target production plan model, and operating the target production plan model to output the product production plan data limited by the output field. According to the invention, the product plan data processing efficiency can be improved.

The invention provides a zero-code report management method and system. The method comprises the following steps: 1) identifying a shot paper table picture to obtain a table title and table items; processing the spreadsheet to obtain a sheet title and a sheet item; 2) processing the obtained table titles and table items to obtain database names and field names, and establishing a database table and in-table fields; outputting the processed database name and field name; 3) dynamically generating report management data according to the input database name and field name so as to realize the functions including adding, deleting, modifying and querying of the report data; 4, the needed UI template is selected according to the input database name and the input field name, and a report management interface and an editing interface are dynamically generated according to the input item and the selected UI template style.The requirement for zero-code report management is met by photographing and recognizing a traditional paper report, importing an electronic report and generating the needed report through one key.

Described are systems and methods for generating a digital rights management (“DRM”)-protected input field of a media content, including receiving, via a first graphical user interface (“GUI”), at least one user input associated with a DRM-protected input field, wherein the DRM-protected input field has been caused to be output via the GUI and is substantially hidden from view, based on the at least one user input, appending at least one DRM-protected media element to the DRM-protected input field via a browser module, and causing to output, via the first GUI, the DRM-protected input field with the appended DRM-protected media such that the appended DRM-protected media is substantially visible via the first GUI.

A method for writing data sets (DS) into a relational database (13), wherein each data set (DS) comprises at least two attributes (A), includes the steps of: determining at least one value for at least one of the attributes (A1) as criterion for filtering the data sets (DS) by the attribute value; computer implemented outputting data sets (DS) filtered by the attribute value in an output view (AS) and providing an input field (EF) in the output view (AS) for entering a value for another one of the attributes (A4); in response to entering a value in the input field (EF) of the output view (AS) computer implemented generating a complete data set (DS4) including the value set as filter criterion for the corresponding attribute (A1) and the entered value for the other attribute (A4); and storing the generated dataset (DS4) in the relational database (13).

The application discloses a large-scale PDE neural operator pre-training method based on a high-frequency enhancement module, a partial differential equation (PDE) data set is composed into a mixed data set, a large-scale PDE neural operator is constructed, preprocessed PDE data is mapped to a latent representation space through a space-time encoder, a frequency decomposition module is used for frequency space mapping, the frequency decomposition module includes parallel high-frequency branches and low-frequency branches, and high-frequency features and low-frequency features are obtained respectively; a multi-frequency fusion module (GFM) adaptively fuses the high-frequency features and the low-frequency features through a gating mechanism; finally, a prediction head is used for processing the fused features, and final output features, i.e., predicted physical features of a next time step, are obtained. The application firstly introduces an explicit frequency division and a high-frequency enhancement mechanism, the input field is divided into low-frequency and high-frequency parts, the low-frequency branches / high-frequency branches are used for processing respectively, and thus the model can simultaneously consider global trend modeling and local gradient detail reconstruction.

The invention provides a chart generation method and device, electronic equipment and a storage medium, and relates to the technical field of data analys.The chart generation method comprises the steps that in response to a data analysis instruction for a target data source, at least one initial analysis intention is displayed; in response to the intention selection instruction, determining a target analysis intention from the at least one initial analysis intention based on the intention selection instruction; displaying a question template corresponding to the target analysis intention; receiving an input field aiming at each first slot position in the question template, and combining the input field with a first fixed statement in the question template to generate a question sentence pattern; and performing chart generation processing on the target data source based on the question sentence pattern to obtain a target chart. By introducing the structured input mode, the user is restrained from asking questions too divergently, the quality of the question sentence pattern is improved, the efficiency and accuracy of chart generation are improved, the generated chart better conforms to the expectation of the user, and the satisfaction degree of the user is improved.

The invention describes a computer-implemented method for generating a parameterization assistant (PA), wherein a host (HO) is provided on which an operating program (BP) comprising a user interface (GUI) is executed, wherein the user interface (GUI) has a plurality of input fields (EF1, EF2, ..., EF8) via which a user (BN) enters application information and / or parameter values ​​for a field device (FG) of the automation technology, wherein the operating program (BP) creates a parameter set for the field device (FG) based on the input of the user (BN), comprising: - Recording a field device type by the operating program (BP); - Recording a plurality of inputs made by the user (BN), wherein the inputs comprise application information and / or parameter values ​​entered into various input fields (EF1, EF2, ..., EF8) of the user interface (GUI); - Saving the recorded inputs made by the user (BN) linked to the field device type; and - Creating the parameterization assistant (PA), wherein for creating the parameterization assistant (PA) the stored inputs of the user (BN) are analyzed and one or more relationships with respect to the inputs on several input fields (EF1, EF2, ..., EF8) are identified, a use of such a parameterization assistant in a method for parameterizing a field device, a computer-readable medium, and a computer system.

A method, computer program product, and computer system for automatic compliant password generation. The method includes activating password generation for a given input field and gathering information from one or more sources associated with the input field. The method includes determining password criteria from the gathered information and generating bound requirements based on the determined password criteria. The method further includes generating a randomized password meeting the bound requirements.

The invention discloses a table instruction conversion system based on an electric energy meter communication protocol, and the system comprises a data collection module which obtains and processes an electric energy meter communication protocol file and a historical manual processing instruction data set; the basic information reading module is used for extracting an input field and a data format and mapping a power grid instruction format to generate a compliance instruction; the instruction missing comparison module is used for comparing the compliance instruction with the historical data set and judging field missing content; the lexicon association and expansion module is used for extracting initial keywords and generating virtual expansion words covering missing scenes; the evaluation storage module is used for verifying the virtual expansion words and storing the virtual expansion words into an expansion associated word bank in a classified manner; the table content information extraction module is used for analyzing the file through an index strategy, automatically extracting content to fill the intelligent table and recording a source; the method has the advantages that electric energy meter communication protocol deep analysis, dynamic lexicon expansion and automatic table instruction generation can be carried out, and electric energy meter data processing refinement and real-time performance are improved.

A diffractive wavefront processor approximates the all-optical phase conjugation (OPC) operation for input fields with phase aberrations. A set of passive diffractive layers was optimized to all-optically process an arbitrary phase-aberrated input field, producing an output field with a phase distribution that is the conjugate of the input wave. Operation of the wavefront processor was experimentally validated by using fabricated diffractive layers trained using deep learning and performing OPC on phase distortions never seen during training. The diffractive wavefront processor successfully performed the OPC task through a shallow volume that axially spans tens of wavelengths. A diffractive phase-conjugate mirror was also created by combining deep learning-optimized diffractive layers with a standard mirror. The diffractive wavefront processor can be used for diverse OPC-related applications, e.g., turbidity suppression and aberration correction, and is also adaptable to different spectral bands of the electromagnetic spectrum.

To provide an information processing system capable of reducing a welfare undertaker's burden of creation of a document.SOLUTION: An information processing system comprises: a record reception section for receiving an interview record recording interview contents between a user who utilizes welfare services and a welfare undertaker who supports the user from a terminal device used by the welfare undertaker; a selection reception section for receiving selection of user information identifying the user when the record reception section receives the interview record; a record acquisition section for acquiring a past interview record recorded in the past relative to the interview record on the basis of user information that the selection reception section receives the selection; a generation instruction section for instructing a text generation AI to generate a text inputted to a document file having predetermined input items on the basis of the interview record and the past interview record; a text acquisition section for acquiring the text generated by the text generation AI; and an output section for outputting a document file in which the text acquired by the text acquisition section is inputted to the input items.SELECTED DRAWING: Figure 1

A method for generating self-serve integrations includes receiving a network address of a configuration file that includes parameters to interface with a server. The method extracts, from the configuration file, endpoints and operation(s) available to manipulate each endpoint. The method displays a first table having a rows displaying (a) a given endpoint and (b) a menu for selecting a given operation to manipulate the given endpoint. The method, upon selection of a given row, displays input field(s) that accept a parameter, authorization, header, body, and / or response data. The method gathers, from the server, a data fields available at the given endpoint. The method displays a second table having rows that have data field(s), and input(s) for a data type, column type, a display name, unit, description, primary key, secondary key, and / or an indexing toggle.