122 results about "Input field" patented technology

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.

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. 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.

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.

The invention relates to the technical field of electrostatic discharge methods, and discloses an electrostatic discharge method capable of dynamic monitoring, and the method comprises the following steps: collecting a video image of a berth working area based on a multi-path camera; updating an electrostatic discharge region (ROI) and an entry detection line (line) in real time from the input field; establishing a unique tracking record for the detected target, and storing a frame sequence of the ROI touched by the left hand and the right hand of the target; if it is detected that the target crosses the detection line from bottom to top, whether a touch behavior reaching the target frame number exists in the corresponding historical sequence or not is judged; if yes, judging that electrostatic discharge exists and not giving an alarm, otherwise, giving an alarm; according to the electrostatic discharge method capable of being dynamically monitored, significant technical progress is achieved in the aspects of algorithm precision, response speed and multi-channel adaptation, stable and reliable automatic detection can be achieved in a complex industrial environment, and an efficient intelligent solution is provided for industrial safety monitoring.

The invention discloses a power construction site operator tracking method, system and device based on deep learning, and a medium, and belongs to the technical field of operator tracking, and the method comprises the steps: collecting an operator image of a construction site, and constructing an operator image set; an operator tracking model based on deep learning is constructed, the on-site operation image is input into the operator tracking model, and the operator tracking model is used for identifying operators on the power construction site and judging behavior types of the operators; based on the operator image set, training an operator tracking model to obtain a trained operator tracking model; and after finishing training the operator tracking model, executing an operator tracking task by using the operator tracking model. Compared with the prior art, the method has the advantages that the target detection efficiency, precision, recognition capability, automatic response capability and the like are improved, a dynamic and rapid changing environment can be effectively handled, and the safety and operation efficiency of operators are improved.

To provide an accuracy maintenance management system, an accuracy maintenance management method, and a program that can improve the accuracy of detecting accuracy degradation in trained models that output inference results based on explanatory variables. [Solution] The accuracy maintenance management system includes a display unit that displays a reception screen on a display device for receiving input operations for inference results output from a trained model into which explanatory variables have been input, or for evaluation results for explanatory variables, and a degradation determination unit that determines whether or not the accuracy of the trained model has deteriorated based on the evaluation results received on the reception screen. The reception screen may include an input field for evaluation results and a display field for explanatory variables. The reception screen may further include a display field for inference results. The index calculation unit may calculate an evaluation index representing the accuracy of the trained model based on the evaluation results received on the reception screen.

1. Name of the product in this design: Input content conversion interactive area of ​​a graphical user interface for displaying and interacting with the input method function of electronic devices. 2. Purpose of this design: An electronic device. 3. The key design features of this product are: the parts in the graphical user interface, and the parts not marked with dotted lines are the parts for which protection is required. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: The overall appearance design of the interface is used for chat dialogue, input method function display, display of generated text images, text image template switching and other interactions; the partial appearance design of the interface is used to convert the content entered in the input field into text-themed image content within the chat page, display the generated text images, text image template switching and other interactions. 7. Human-computer interaction method of graphical user interface: In the main view of Design 1, users can click the "Save" control to save the generated text image, or click the "Send" control to send the generated text image; they can click the cross in the upper right corner to exit the "Text Image" function; they can also click to select any rectangular text image template and switch to preview the layout style of the text under different templates. Design 2 uses the same human-computer interaction method as Design 1. In the main view of Design 3, users can click the "Save" control to save the generated text image, or click the "Send" control to send the generated text image; they can click the cross in the upper right corner to exit the "Text Image" function; they can also click to select any rectangular text image template (or slide the preview area in the middle to the left) to switch the layout style of the text under different templates. Design 4 uses the same human-computer interaction method as Design 3. In the Design 5 main view, when the user enters text in the input field and clicks the "Text Image" function control in the input method toolbar, a text image with the entered text as the theme is automatically generated, showing the interface change from the Design 5 main view to the Design 5 interface change state diagram. In the Design 6 main view, when the user enters text in the input field (the "Text Image" function is enabled), a text image based on the entered text is automatically generated, showing the interface changes from the Design 6 main view to the Design 6 interface state diagram. In the Design 7 main view, the user has entered text content in the input field of the "Text Image" function. When the user clicks the "Enter" control in the lower right corner of the input field, a text image with the entered text content as the theme is automatically generated, showing the interface change from the Design 7 main view to the Design 7 interface change state diagram.

The invention relates to a pipetting device with a touch screen and a system with such a pipetting device. The operating concept of the pipetting device provides that values of pipetting parameters can be set by a user on at least one input screen page, actuation of a control element leads to the display of an output screen page and the initiation of a pipetting process defined by the pipetting parameters, and touching of an individual input field of the output screen page leads back to the input screen page.

An apparatus includes one or more light guides. The apparatus also includes a first in-coupling element configured to in-couple first light having a first input field of view (“FOV”) into a first light guide, and a second in-coupling element configured to in-couple second light having a second input FOV into a second light guide. The apparatus also includes a first out-coupling element configured to out-couple the first light from the first light guide as first output light having a first output FOV, and a second out-coupling element configured to out-couple the second light from the second light guide as second output light having a second output FOV that is substantially non-overlapping with the first output FOV. A combination of the first output FOV and the second output FOV is greater than at least one of the first output FOV or the second output FOV.

[Problem] To provide a creation assistance tool that enables easy, stress-free, and rapid creation of a cause-and-effect diagram. [Solution] A cause-and-effect diagram creation system comprises: a first display unit that displays an input unit in which a plurality of input fields are displayed in a first hierarchical structure in a tree format; a second display unit that displays a cause-and-effect diagram in a second hierarchical structure in a tree format; and an information processing unit that, on the basis of text information input to the input fields in the first display unit, creates the cause-and-effect diagram configured such that levels of the first hierarchical structure and levels of the second hierarchical structure are in one-to-one correspondence, and causes the second display unit to display the cause-and-effect diagram.

A method for managing network services for a cellular network provider including GUI including a search input field and a subscriber identifier selection field. The method includes receiving a user selection of an ICCID identifier type via the subscriber identifier selection field and a query input of an ICCID number associated with a subscriber. Based on the user selection of the ICCID identifier type, the method includes querying a switch control using the ICCID number received. In response, the method includes receiving a first set of subscriber information including an IMSI number associated with the subscriber. In response, the method includes querying a first additional system using the IMSI number and receiving, from the first additional system, a second set of subscriber information associated with the subscriber. The method includes populating one or more fields of the GUI with the first and second set of subscriber information.

Apparatus, methods and systems for leveraging artificial intelligence to generate and enforce a tripartite smart contract are provided. A contract executor may receive a command from an applicant to generate a tripartite smart contract between the applicant and a beneficiary. The contract executor may generate input fields that request information from the applicant. The contract executor may identify one or more successfully executed tripartite smart contracts that include data that corresponds to inputs received from the applicant. The contract executor may generate an executable tripartite smart contract using terminology associated with the identified successfully executed tripartite smart contracts and the inputs. The executable tripartite smart contract may be transmitted to the applicant, the beneficiary and the contract executor for signing. In response to receiving a signature from the applicant, the beneficiary and an entity associated with the contract executor, an issued tripartite smart contract may be generated.

In some embodiments, an electronic device communicates input fields of an application user interface in accordance with a respective application user interface update message. In some embodiments, the electronic device communicates an input field of an application user interface according to a location sharing application user interface update message. In some embodiments, the electronic device transmits an input field of the application user interface according to an audio message application user interface update message.

The invention relates to a nuclear reactor fault diagnosis method and device. The method comprises the steps that characteristic parameters of a nuclear reactor are obtained, and the characteristic parameters comprise a reactor core geometric code and a flow channel network topological structure; inputting the characteristic parameters into a preset fault diagnosis model for fault diagnosis to obtain a diagnosis result; the fault diagnosis model comprises a generator, a discriminator and a fault recognizer; the generator is used for generating various types of field data, and the discriminator is used for evaluating whether the various types of field data meet physical constraints or not; the fault recognizer is used for carrying out fault recognition based on the input field data. The discriminator is arranged in the fault diagnosis model to judge whether the field data conforms to the physical constraint or not, it is ensured that the characteristic data of the nuclear power plant follows the basic physical constraint rule, finally, further fault recognition is conducted on the field data conforming to the physical constraint based on the fault recognizer, and the accuracy of the nuclear reactor fault diagnosis result is improved.

The invention discloses a query response and code generation method and system based on power field document analysis, and the method comprises the steps: carrying out the analysis and preprocessing of an input field document, and constructing a document text logic diagram; constructing a domain knowledge graph; receiving user query, and executing structure matching retrieval based on a document text logic diagram and association reasoning retrieval based on a domain knowledge graph to form a traceable evidence packet; constructing a structure enhancement context based on the evidence packet, inputting the structure enhancement context into a domain language large model, and generating a response containing a natural language description and a structured domain language code; and performing instant compilation and tensor simulation verification on the structured domain language code, triggering retrieval and generated closed-loop correction based on deviation information when the verification is not passed, and outputting an analysis result and the code when the verification is passed. According to the method, the accuracy, interpretability and output reliability of long document processing in the electric power field are improved.

This invention provides a web-based input support system and program that allows users to easily input data into a web-based application form based on an overview of the completed application form on the web screen. [Solution] The web screen input support system and program involves a web screen input support server 1 reading the basic data of the application form on the web screen, the input data for the input fields of the application form, and the attached files or linked information attached to the application into a generating AI 3 to generate summary data for the web screen. The inputter terminal 4 searches through the generated summary data, and the generating AI 3 learns from the input data previously entered in the application form for the selected summary data. The system then generates the optimal input data for the inputter and sets it in the application form on the web screen of the web screen providing server 2.

1. Name of the product in this design: The main body of the audio search graphical user interface for electronic devices. 2. Purpose of this design: An electronic device. 3. The key design features of this product are the graphical user interface in the electronic device for which protection is sought. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: The graphical user interface is used to search for audio. The graphical user interface requests protection for a portion used to switch the audio search interface, search for audio, display audio information, and play audio. 7. Human-computer interaction method of graphical user interface: In response to the user touching or clicking the "Ai" button at the top or swiping the "Listen" button at the top to the right in the main view of Design 1, the graphical user interface changes from the main view of Design 1 to Design 1 Change State Diagram 1, then to Design 1 Change State Diagram 2, and then to Design 1 Change State Diagram 3 to show the process of switching to the audio search page; In response to the user touching or clicking the question in the interactive display area or entering and sending a question in the input field in Design 1 Change State Diagram 3, the graphical user interface changes from Design 1 Change State Diagram 3 to Design 1 Change State Diagram 4, then to Design 1 Change State Diagram 5, then to Design 1 Change State Diagram 6, and then to Design 1 Change State Diagram 7 to show the audio search results; In response to the user touching or clicking the "Add to Playlist" button in Design 1 Change State Diagram 7, the graphical user interface changes from Design 1 Change State Diagram 7 to Design 1 Change State Diagram 8 to show the updated playlist. In response to a user touching or clicking the "Ai" button at the top or swiping right on the "Listen" button at the top in the main view of Design 2, the graphical user interface changes from the main view of Design 2 to Design 2 Change State Diagram 1, then to Design 2 Change State Diagram 2 to demonstrate the process of switching to the audio search page; in response to a user touching or clicking a question in the interactive display area or entering a question in the input field and sending it in Design 2 Change State Diagram 2, the graphical user interface changes from Design 2 Change State Diagram 2 to Design 2 Change State Diagram 3, then to Design 2 Change State Diagram 4, then to Design 2 Change State Diagram 5, then to Design 2 Change State Diagram 6 to display the audio search results; in response to a user touching or clicking the "Add to Playlist" button in Design 2 Change State Diagram 6, the graphical user interface changes from Design 2 Change State Diagram 6 to Design 2 Change State Diagram 7 to display the updated playlist. In response to a user touching or clicking the "Ai" button at the top or swiping right on the "Listen" button at the top in the main view of Design 3, the graphical user interface changes from the main view of Design 3 to Design 3 Change State Diagram 1, then to Design 3 Change State Diagram 2 to demonstrate the process of switching to the audio search page; in response to a user touching or clicking a question in the interactive display area or entering a question in the input field and sending it in Design 3 Change State Diagram 2, the graphical user interface changes from Design 3 Change State Diagram 2 to Design 3 Change State Diagram 3, then to Design 3 Change State Diagram 4, then to Design 3 Change State Diagram 5 to display the audio search results; in response to a user touching or clicking the "Add to Playlist" button in Design 3 Change State Diagram 5, the graphical user interface changes from Design 3 Change State Diagram 5 to Design 3 Change State Diagram 6 to display the updated playlist. In response to a user touching or clicking the "Ai" button at the top or swiping right on the "Listen" button at the top in the main view of Design 4, the graphical user interface changes from the main view of Design 4 to Design 4 Change State Diagram 1, and then to Design 4 Change State Diagram 2 to demonstrate the process of switching to the audio search page; in response to a user touching or clicking a question in the interactive display area or entering a question in the input field and sending it in Design 4 Change State Diagram 2, the graphical user interface changes from Design 4 Change State Diagram 2 to Design 4 Change State Diagram 3, and then to Design 4 Change State Diagram 4 to display the audio search results; in response to a user touching or clicking the "Add to Playlist" button in Design 4 Change State Diagram 4, the graphical user interface changes from Design 4 Change State Diagram 4 to Design 4 Change State Diagram 5 to display the updated playlist. In response to a user touching or clicking the "Ai" button at the top or swiping right on the "Listen" button at the top in the main view of Design 5, the graphical user interface changes from the main view of Design 5 to Design 5 Change State Diagram 1, and then to Design 5 Change State Diagram 2 to demonstrate the process of switching to the audio search page; in response to a user touching or clicking a question in the interactive display area or entering a question in the input field and sending it in Design 5 Change State Diagram 2, the graphical user interface changes from Design 5 Change State Diagram 2 to Design 5 Change State Diagram 3, and then to Design 5 Change State Diagram 4 to display the audio search results. In response to a user touching or clicking the "Ai" button at the top or swiping right on the "Listen" button at the top in the main view of Design 6, the graphical user interface changes from the main view of Design 6 to Design 6 Change State Diagram 1, and then to Design 6 Change State Diagram 2 to demonstrate the process of switching to the audio search page; in response to a user touching or clicking on a question in the interactive display area or entering a question in the input field and sending it in Design 6 Change State Diagram 2, the graphical user interface changes from Design 6 Change State Diagram 2 to Design 6 Change State Diagram 3, then to Design 6 Change State Diagram 4, and then to Design 6 Change State Diagram 5 to display the audio search results. 8. Other situations requiring explanation: The portions of the graphical user interface shown by the dashed lines in the views of Design 1 to Design 6 do not constitute the parts protected by this design.

A unified framework system and method for a computer implemented artificial intelligent assistant to perform multiple tasks for remote sensing, includes a task input field for receiving a task identity, a global image encoder configured to receive a remote-sensing image and a user query and encode patch-level tokens at a high resolution via interpolation positional encodings, an MLP adapter configured to receive the patch-level tokens and adapt the tokens to language space, and a large language model configured to generate natural language responses interleaved with corresponding object locations based on the language space and task specific prompts. The global image encoder further includes a region input field for receiving region location parameters. The framework system is configured to switch based on the input task identity between different types of remote sensing visual interpretation tasks.

An information processing system, method, and program are provided that improve convenience when considering M&A. [Solution] The method includes displaying a first input format for inputting first project information related to a transaction between an organization and a trading partner, accepting input of the first project information into the first input format from a seller of the organization or an entity acting on its behalf, controlling the display so that the first project information is not displayed to a buyer of the organization, and accepting input of second project information into a second input format for inputting second project information from the seller. The second input format is capable of accepting input of information relating to items not included in the first input format as at least part of the second project information, displaying the second input format with at least part of the first project information transcribed into corresponding input fields in the second input format, and controlling the display so that at least part of the second project information is displayable to the buyer after the second project information is input.

The application discloses a general-purpose computer hologram generation method and system based on structured propagation, equipment, medium and product, and relates to the field of computer holography. The method comprises the following steps: decoupling a zero-frequency reference diagonal spectrum method transfer function to construct a structured propagation model; obtaining a target scene graph and a laser wavelength; based on the target scene graph and the laser wavelength, a structured propagation model is used to obtain a structure normalized input field; the structure normalized input field is input into a hologram generation model to obtain a pure phase hologram; and the hologram generation model is obtained by training a U-net network through a sample input field and a sample pure phase hologram. The application can improve the accuracy of hologram generation.

Systems and methods may be provided for masking data on public networks, such as social networking sites. At a publishing node, the system may monitor data input fields in a webpage, and intercept and encode content, such as text, images, and video input at the data input fields, prior to the content being posted online on a public service provider's website. A privacy agent may process input field content to try to detect encoding markers in the input field content, which define portions of the content that are to be encoded. A third party key server may be used to store decoding keys. A URI reference to the decoding key may be used to access the decoding key by a node attempting to view the decoded version of the input field content.