251 results about "Input field" patented technology

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.

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.

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.

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 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 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.

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.

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.

In one implementation, a method of visualizing text is performed by a device including a display, one or more processors, and non-transitory memory. The method includes detecting a text input device at a first location within a volumetric environment. The method includes detecting selection of a text input field of a user interface displayed within the volumetric environment. The method includes displaying, on the display, a representation of the text input field at a second location within the volumetric environment associated with the first location of the text input device.

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.

The invention provides a sensor deployment optimization method based on a field environment, and the method comprises the steps: a big language model analysis step: carrying out the analysis of an input field environment parameter and an optimization target through a big language model, and generating a first mathematical model for sensor deployment; a multi-agent collaborative optimization step: dynamically adjusting the first mathematical model through a multi-agent collaborative mechanism, and generating an initial deployment scheme of the sensor; and a genetic algorithm optimization step: performing multi-objective optimization on the initial deployment scheme through a genetic algorithm, and outputting the deployment number and deployment positions of the optimized sensors. The invention further provides a sensor deployment optimization device based on the field environment, a storage medium and electronic equipment. Therefore, by combining the large language model, the multi-agent cooperation mechanism and the genetic algorithm, global optimization and dynamic adjustment of the deployment number and the deployment positions of the sensors are realized, so that the deployment efficiency and effect of the sensors in the field environment are greatly improved.

Disclosed herein are system, method, and computer program product aspects for generating a prompt for an LLM using a prompt template. A system retrieves an external data reference to context data included in a prompt template. The prompt template is selected from a plurality of prompt templates based on the field type of an input field in an interface. The system then generates a prompt based on the prompt template and the retrieved context data. The system then prompts the LLM accordingly, which generates a non-deterministic output for responding to the user request.

Based on questions posed to users in specific fields and their answers, appropriate feedback is created that is tailored to the user's characteristics as reflected in their responses. [Solution] The information processing device comprises: an input form transmission unit that transmits an input form to a user terminal which includes at least input fields for inputting questions in a specific field to the user and answers to those questions; an answer receiving unit that receives answers entered by the user into the input form via the user terminal; a feedback creation unit that creates feedback to the user which includes at least one of evaluation, advice, and suggestions according to the content of the answers; and a feedback transmission unit that transmits the feedback created by the feedback creation unit to the user terminal.

This electronic device comprises a memory for storing instructions, a display, and at least one processor including processing circuitry. The instructions, when executed individually or collectively by the at least one processor, cause the electronic device to: when a first user command for capturing a first screen of the display is identified, acquire a captured image of the first screen and additional information related to the first screen; when a text included in the captured image is identified, convert the identified text into structured text data on the basis of the additional information; acquire paste content on the basis of the structured text data and context information about a second screen of the display; and input the paste content to an input field included in the second screen.

1. Name of the product of this design: The main body of an interactive graphical user interface for changing the number of an electronic device. 2. Purpose of this design product: an electronic device. 3. The key design features of this design product lie in the part within the graphical user interface, and the non-dashed line portion is the part for which protection is sought. 4. The picture or photo that best illustrates the key points of the design: Main view of Design 1. 5. Designate Design 1 as the base design. 6. Purpose of the Graphical User Interface: The entire interface is used to change and modify the number bound to the automatic recharge function, change prompts, etc.; the purpose of the local part of the interface is the same as the overall purpose. 7. Human-computer interaction method of the graphical user interface: In the main view of Design 1, the user can click the cross on the right side of the number input field to delete the number with one click, click to select the corresponding label to set the number, click the "Select from Address Book" control to select the number; and pull down the interface to close the floating layer for changing the number. In the main view of Design 2, users can click on the number input bar to enter a number, click on the corresponding label to set the number, click on the "Select from Address Book" control to select a number; and pull down the interface to close the change number pop-up. The human-computer interaction method of Design 3 is the same as that of Design 2. The human-computer interaction method of Design 4 is the same as that of Design 1, and it prompts that the number filled in does not meet the specifications.

In one aspect, a computerized system comprising: a user-interface configured to: display a skin color selection, wherein the skin color selection comprises a plurality of skin pigments, receive a user skin color selection, display a skin cancer familial history input field, receive a skin cancer familial history input value, display a sun protection factor (SPF) input field, receive a SPF sunscreen input value selection for sunscreen being used; a sun exposure monitoring application operating in the computer system configured to: translate the skin color selection to a maxim sun exposure value, and computer a maximum sun exposure time using the user skin color selection, the skin cancer familial history input value, and the SPF selection for a sunscreen being used, monitor a sun exposure of the computer system, implement an alert signal when the maximum sun exposure time is reached.

1. The name of the design product: input area and display area of information search graphical user interface of electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: the partial graphical user interface of the electronic device. 4. The picture or photo that best shows the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the graphical user interface is used for information search. The partial graphical user interface protected by the design is used to input search instructions and display recommended search instructions and generated answer results. 7. The human-computer interaction mode of the graphical user interface: in response to the user inputting search keywords in the input bar of the design 1 front view, the graphical user interface changes from the design 1 front view to the design 1 change state view 1 to display the associated recommended search terms; in response to the user inputting search instructions in the input bar of the design 1 change state view 1, the graphical user interface changes from the design 1 change state view 1 to the design 1 change state view 2 to display the generated answer results for the instructions. In response to the user inputting search instructions in the input bar of the design 2 front view, the graphical user interface changes from the design 2 front view to the design 2 change state view to display the generated answer results for the instructions. In response to the user inputting search keywords in the input bar of the design 3 front view, the graphical user interface changes from the design 3 front view to the design 3 change state view 1 to display the associated recommended search terms; in response to the user inputting search instructions in the input bar of the design 3 change state view 1, the graphical user interface changes from the design 3 change state view 1 to the design 3 change state view 2 to display the generated answer results for the instructions. In response to the user inputting search instructions in the input bar of the design 4 front view, the graphical user interface changes from the design 4 front view to the design 4 change state view to display the generated answer results for the instructions. 8. Other circumstances that need to be explained: the part of the graphical user interface shown by the dashed line in each view of designs 1 to 4 does not constitute the part protected by the design.

The invention provides an ocean hypoxia prediction method and device, computer equipment and a program product, and the method comprises the steps: obtaining mode drive input fields of a target sea area at different times; utilizing a plurality of coupling models in a preset ocean hypoxia forecasting model to perform identification and prediction processing on the mode driving input fields at different time to obtain a three-dimensional ocean physical state field, a biogeochemical state field and a three-dimensional dissolved oxygen concentration state field of the target sea area in a first preset time period in the future; according to the target time interval, marine environment forecast information of the target sea area in a first preset time period in the future is generated and broadcasted in a rolling mode; and extracting a target dissolved oxygen concentration state field matched with a preset area of the target sea area in the three-dimensional dissolved oxygen concentration state field, and determining oxygen deficit indication information in the preset area and generating visual oxygen deficit forecast information according to the target dissolved oxygen concentration state field and different oxygen deficit thresholds.

The invention discloses a large-scale PDE neural operator pre-training method based on a high-frequency enhancement module, and the method comprises the steps: forming a mixed data set through partial differential equation PDE data, constructing a large-scale PDE neural operator, mapping the preprocessed PDE data to a potential representation space through a space-time encoder, carrying out the frequency space mapping of the data through a frequency decomposition module, and carrying out the pre-training of the large-scale PDE neural operator. The frequency decomposition module comprises a high-frequency branch and a low-frequency branch which are parallel to obtain high-frequency features and low-frequency features respectively; the multi-frequency fusion module GFM adaptively fuses the high-frequency features and the low-frequency features through a gating mechanism; and finally, the fused features are processed through a prediction head, and final output features, namely predicted physical features of the next time step, are obtained. According to the method, an explicit frequency division and high-frequency enhancement mechanism is introduced for the first time, an input field is decomposed into a low-frequency part and a high-frequency part, and a low-frequency branch and a high-frequency branch are adopted for processing, so that the model can give consideration to global trend modeling and local gradient detail reconstruction at the same time.

The application belongs to the field of sub-seasonal climate prediction, and provides a sub-seasonal climate prediction method and system based on the combination of dynamic model downscaling and machine learning downscaling, which comprises the following steps: S1, generating initial field and model boundary field information required for dynamic downscaling based on global climate model output data; S2, driving regional climate model to perform dynamic downscaling by using the initial field and model boundary field information; S3, generating input field required for machine learning downscaling based on the output circulation field information of the regional climate model; S4, performing machine learning downscaling correction optimization on the output circulation field of dynamic downscaling based on a convolution model; S5, performing machine learning super-resolution based on the output data of machine learning downscaling correction; and S6, generating sub-seasonal prediction information of double downscaling of dynamic model and machine learning. The application utilizes the complementary advantages of dynamic downscaling and deep learning downscaling, improves the sub-seasonal prediction skill, and copes with new challenges brought by climate change.

The present disclosure provides a method, device, computer equipment and program product for predicting marine hypoxia, wherein the method comprises: obtaining a mode-driven input field of a target sea area at different times; using a plurality of coupled models in a preset marine hypoxia prediction model to respectively identify and predict the mode-driven input field at different times, to obtain a three-dimensional marine physical state field, a biogeochemical state field and a three-dimensional dissolved oxygen concentration state field of the target sea area within a first preset time period in the future; generating marine environment prediction information of the target sea area within the first preset time period in the future according to a target time interval and rolling broadcasting; extracting a target dissolved oxygen concentration state field matched with a preset region of the target sea area from the three-dimensional dissolved oxygen concentration state field, and determining hypoxia indication information in the preset region and generating visual hypoxia prediction information according to the target dissolved oxygen concentration state field and different hypoxia thresholds.

Systems, computer program products, and methods are described herein for electronically augmenting resource distribution commands and facilitating transfer of resources. The present invention may be configured to display, via a user device and to a user, a graphical user interface including input fields for providing commands to perform a resource distribution and receive, from the user and via the graphical user interface displayed via the user device, a single user input at the graphical user interface. The present invention may be configured to, in response to receiving the single user input, automatically identify, based on historical resource distribution data associated with the user, inputs corresponding to each of the input fields and display, via the graphical user interface displayed via the user device and in each input field of the input fields, an input, of the inputs, corresponding to the input field to complete the commands.

This invention discloses a method for dynamic prediction of reservoir production that integrates discrete gradient information, belonging to the interdisciplinary field of reservoir development and artificial intelligence. The steps are as follows: First, a numerical simulation dataset for oil-water two-phase flow in heterogeneous reservoirs is constructed based on numerical simulation methods. Second, a dual-branch network structure is designed to extract the spatial and physical features of the input field data in parallel, including a main feature encoding branch and a difference operator branch. Third, a backbone network is designed for deep nonlinear modeling. Fourth, an efficient pressure and saturation field prediction neural network model is constructed based on the dual-branch network structure and the backbone network. During the model training phase, spatial observation points from some time steps are used to participate in the calculation of data loss terms, while the residuals of the physical control equations are introduced as physical loss terms at all time steps and throughout the entire space. Finally, a well-trained efficient pressure and saturation field prediction neural network model is obtained, achieving high-precision prediction of pressure and saturation fields across the entire time series.

The present application relates to a kind of information recovery methods based on scattering system, belong to spectral data processing technical field.The method is: the scattering characteristic of scattering system is calculated;Using the scattering characteristic calculated, establish scattering signal self-excitation amplification mechanism;On the scattering signal self-excitation amplification mechanism, incident light field time domain, space domain, frequency domain coding and trend decoding, wave analysis, to nearly completely recover scattering information;Using negative correlation statistical operation obtains the accurate scattering information of high noise scattering system.The present application is amplified by the scattering signal of special self-excitation method, based on light field composite coding and scattering information trend analysis, accurately judges input field information;By introducing negative correlation operation, can nearly completely recover incident field information, realize the nearly complete evaluation of the scattering characteristic of extremely high noise system.The present application promotes the progress of imaging technology not limited by the thickness of scattering medium, further promotes the development of realizing human clinical high-resolution optical reflection, transmission imaging.

An example embodiment may include: a display; a memory storing instructions; and a processor. The instructions stored in the memory, when executed by the processor(s), may cause the electronic device to: display an input field in response to a first user input calling the input field; acquire a second user input that is input to the input field; display the acquired second user input as text in the input field; and analyze the content of the text and control at least one actionable item for processing the analyzed content so that the actionable item is displayed to with at least a portion of the text via the display, wherein the at least one actionable item may include at least one of an actionable object of an application, an actionable object providing a function in the application, an action preview based on generative artificial intelligence (AI), or a setting object of the electronic device.