76 results about "Application computers" patented technology

The invention relates to the technical field of information, in particular to a forming process and system of a high-precision injection hook in the technical field of injection hook forming. The forming process includes the steps that computer aided design and finite element analysis are applied, the forming process of the injection hook in a mold is simulated, the mold structure is optimized, and the mold testing frequency is reduced; a high-precision mold is integrated with a cooling channel of a preset ejection hook arrow-shaped structure, a temperature sensor is arranged in the cooling channel, the cooling state is monitored in real time, cooling parameters are adjusted based on monitoring data, and precise structure forming is achieved. And the machine vision system detects the integrity and direction consistency of the arrow-shaped structure of the molded ejection hook on line, identifies unqualified products, automatically removes the unqualified products, records defect types, and sends defect type data and corresponding product batch information to the production data acquisition module.

A computer-implemented system for multidimensional generative value assessment and applicant selection, consisting of: a data collection unit configured to electronically receive applicant data consisting of structured academic records, work experience records, digital documentation, and unstructured narrative responses generated from generative self-assessment instruments and contextual interviews; a feature extraction unit coupled to the data acquisition unit, configured to apply computer-assisted text processing, semantic analysis, and token-level attribute identification to transform narrative responses and structured data into multidimensional feature vectors that represent generative indicators of innovation, mentoring, collaborative performance, resilience, social contribution, ethical consistency, and predicted institutional impact; a weighting calculation unit configured to assign weight values ​​to the extracted feature vectors based on a digital generative profile definition matrix that includes dimensions, sub-criteria, indicators, documentation requirements and importance coefficients, with the weighting being distributed across the generative dimensions defined in the digital matrix and configurable according to the institutional context; a quantitative rating unit configured to calculate a generative rating score by aggregating weighted feature vectors derived from self-assessment inputs, interview-based ratings, document analyses, and authenticity predictions, with the aggregation including normalization, nonlinearity correction, conflict handling, and artifact frequency balancing to obtain a consolidated score; a proof verification unit configured to electronically validate referenced digital evidence by performing content extraction, metadata verification, pattern matching, and cross-document correlation to determine authenticity, credibility, and contextual relevance with respect to the calculated feature vectors; a classification determination unit configured to assign a classification level to an applicant by comparing the generative assessment score with a set of system-defined calculation thresholds, including at least a lower threshold, a middle threshold and an upper threshold, the classification levels representing different generative maturity states and determining subsequent eligibility for selection; a decision generation unit configured to produce a digital output data set that includes classification level, feature aggregation summaries, evidence validation results, and recommended organizational actions, wherein the decision generation unit encodes the data set in a digitally signed, tamper-proof format and stores it on a non-volatile storage medium; and A system control unit acts as an operational interface to all other units and is configured to orchestrate data flow, scheduling, process state transitions, and event logging to ensure verifiable traceability, consistency, and auditability of the evaluation and selection processes.

The invention discloses a diffusion model and explicit constraint guidance fused visual navigation method and system. The method comprises the following steps: performing feature extraction on visual observation data to obtain target observation semantic features; performing feature extraction on the navigation target data to obtain target image features; performing feature fusion on the target observation semantic feature and the target image feature to generate a condition vector; inputting the condition vectors into a condition diffusion model for diffusion training to generate a plurality of initial candidate paths; constructing an explicit constraint based on the initial image data, and performing path optimization on each initial candidate path according to the explicit constraint to obtain a plurality of candidate optimization paths; the explicit constraints comprise collision constraints and target distance constraints; and determining a target navigation path from each candidate optimization path according to a path selection strategy. According to the method, the problems of insufficient path safety and poor dynamic adaptability can be solved, the safety and accessibility of the path are remarkably improved, the path navigation efficiency is further improved, and the method can be widely applied to the technical field of computers.

According to some embodiments, systems and methods are provided, comprising a classification data store that contains electronic records associated with entity classifications; and the back-end application computer server, coupled to the classification data store, including: a computer processor; and a memory coupled to the computer processor and storing instructions that, when executed by the computer processor, cause the back-end application computer server to: receive a name and an address associated with the name; receive third-party data associated with the name; classify the name as an enterprise type using a classification tool and the third-party data, the classification tool including a trained hybrid machine learning (ML) model; a communication port coupled to the back-end application computer server to facilitate an exchange of data with a remote device via a distributed communication network to support interactive user interface displays that include information about the classification. Numerous other aspects are provided.

A method and system for semantic-based navigation of temporally sequenced content such as videos interprets the image and audio-based content by applying computer-implemented neural networks and performs multi-modal inferences of temporally aligned content. The multi-modal inferences may be performed by means of the application of vectorized embeddings and / or by application of semantic chaining techniques. The multi-modal inferences are applied to generate navigational indicators and / or responses to user inputs that comprise natural language or images. The navigational indicators and responses to user inputs may be personalized based upon user behaviors.

An enterprise risk relationship document back-end application computer server receives a risk relationship document request associated with a particular risk relationship identifier. Responsive to the risk relationship document request, the computer server retrieves information from a risk relationship data store. The risk relationship data store may, for example, contain electronic records for a plurality of risk relationships between the enterprise and parties, and, for each risk relationship, a risk relationship identifier, a party identifier, a communication address, and at least one risk relationship parameter. Based on the retrieved information, a risk relationship document may be automatically created. The computer server may automatically establish a communication link and transmit information about the risk relationship document to the communication address associated with the particular risk relationship identifier. The computer server may also exchange data with a remote device to support interactive user interface displays that include information about the risk relationship document.

A user-described virtual environment method, system, and apparatus obtains a representation of an object and receives a natural language-based communication from a user requesting that a computer-implemented system embody the object within a virtual environment that is described by the user. The natural language description of the virtual environment is interpreted by applying a computer-implemented trained neural network A video stream that embodies the object within a computer-generated virtual environment that is in accordance with the user-described virtual environment is generated by applying a trained neural network and then delivered to the user. The user may then describe desired modifications to the virtual environment and a second video stream is generated in accordance with the desired modifications.

The invention discloses a tensor convolution calculation method and device, equipment, a storage medium and a program product, and relates to the technical field of application computers, and the method comprises the steps: obtaining to-be-transmitted tensor information of a source arithmetic logic unit, and constructing transmission data according to at least two tensor elements in the tensor information; transmitting the tensor element to the destination arithmetic logic unit based on the transmission; and performing convolution operation on the tensor elements in the target arithmetic logic unit. According to the embodiment of the invention, by adopting a mode of splicing the tensor elements, any additional data transmission device does not need to be additionally arranged between the arithmetic logic units, the optimization of transmission data is realized, and by reducing the transmission quantity of the tensor elements, the problem of transmission blockage is relieved, the utilization rate of transmission bandwidth is improved, and the transmission efficiency is improved. According to the method, different types of input data can be processed, the universality of convolution calculation is enhanced, convolution calculation of tensor elements is carried out based on the spliced transmission data, the convolution calculation speed is increased, and the calculation performance is improved.

The invention discloses a computer information security management method and system based on big data, and relates to the technical field of information security management, and the method comprises the steps: carrying out the risk recognition of financial transaction application computer storage data, marking a key transaction concerned object, carrying out the first verification, and marking an abnormal computer information condition; according to the marked abnormal computer information condition, identifying and marking the financial computer information abnormity type with the highest matching degree, and then carrying out second verification to judge whether the financial computer information abnormity type exists or not; when the financial computer information exception type does not exist, obtaining related verification data for third verification; based on the third verification result, whether security approval passes is judged, if the security approval passes, a manual inspection demand is triggered, an abnormal specific reason marked by manual inspection is obtained, and an abnormal label is created for the abnormal specific reason. The multi-level security verification and intelligent abnormity management are realized, and the transaction security and the user experience are significantly improved.

Some embodiments are directed to a resource allocation analysis system implemented via a back-end application computer server. A resource data store may contain electronic records associated with a set of resource types, each electronic record including an electronic record identifier and resource parameter. The back-end application computer server may receive, from the resource data store, information about a set of resource types to be analyzed, including the associated resource parameters. The computer server may then execute a differential evolutionary algorithm to optimize the set of resource types based on at least one non-linear constraint and generate resource analysis results. The back-end application computer server may, according to some embodiments, perform a resampling process that uses non-parameterized historical data, regression on at least one resource type, and moment matching.

A cold rotting device (10) in the manner of a worm composter, particularly for kitchen waste, particularly suitable for indoor spaces and private households, configured to provide a habitat for worms decomposing kitchen waste, comprising a cavity (11) receiving the kitchen waste and providing the habitat, and at least one partition (12, 12a) segmenting or sealing off the cavity, which partition can be positioned at a plurality of, in particular, form-fitting, predefined spatial separation positions or separation lines (13) on / in the cavity (11); characterized in that the plurality of predefined spatial separation positions or separation lines (13) segment the cavity (11) in at least one horizontal spatial direction (u) and, when the partition (12, 12a) is positioned there, each seals off the worms against horizontal migration.

A back-end application computer server may receive a risk relationship analysis request from a user device. The computer server may then extract and summarize information, by a data extractor using deep learning and natural language processing from multiple data sources (including knowledge graphs, websites, and historical loss reports). A response generator may then generate an accurate and contextually relevant response based on the extracted data and information in a risk relationship data store. The risk relationship data store may, for example, contain electronic records associated with a plurality of risk relationships between the enterprise and parties. The relevant response can then be transmitted to the user device.

Computer-implemented methods and systems for integrating computer applications are disclosed. One method includes querying a primary computer application for current state of a newly created object; receiving the current state of the object, and generating object data for a secondary computer application based on the current state of the object. The method further includes communicating an object creation request to a secondary computer application, the object creation request including the generated object data, receiving a secondary computer application object identifier from the secondary computer application upon creation of the object at the secondary computer application, and communicating the secondary computer application object identifier to the primary computer application for storing in a record of the object created at the primary computer application.

The present invention relates to an automatic response device, method, and computer program product for automatic response. The automatic response device (6) comprises: a candidate determination unit (31) that determines a plurality of candidate responses that are likely to be requested by the passenger based on at least one of past response history to speech made by a passenger of the vehicle (1), external information, and internal information, and determines, with respect to each candidate response, a combination of hypothetical speech data representing the assumed speech content when the response is requested and command data for executing the response; an identification unit (32) that identifies the speech content of the passenger from voice signals collected by a microphone (4) provided in the vehicle (1); a selection unit (33) that selects the candidate response from the plurality of candidate responses that corresponds to the hypothetical speech data most consistent with the identified speech content; and a response processing unit (34) that executes a response that follows the command data regarding the selected candidate response.

A computer program comprising instructions which, when executed by a computing device (110, 750) comprising a memory (220, 764) storing a non-browser application (226) and a browser application (222), wherein the non-browser application and the browser application are separate applications with separate user interfaces, wherein the browser application is configured to retrieve web content from a web server and display the web content in a browser tab, cause the computing device (110, 750) to perform operations, wherein the operations include: Execution (410, 510) of the non-browser application (226) on the computing device (110, 750); Display (420, 520) application content including a connection to the web content by the non-browser application on a display of the computing device; Receiving (430, 550) a notification that the connection displayed by the non-browser application has been selected; In response to the indication that the connection has been selected, mapping (440, 560) a browser tab of the browser application to the non-browser application, wherein the mapped browser tab includes the following: a first selectable item associated with an action of the non-browser application, wherein a selection of the first selectable item causes the computing device to perform the action of the non-browser application, wherein the action of the non-browser application involves an operation or task of the non-browser application; and a second selectable item associated with an action of the browser application, wherein a selection of the second selectable item causes the computing device to perform the action of the browser application, the action of the non-browser application involving an operation or task of the browser application; and Displaying (450, 570) the associated browser tab containing the web content within a user interface of the non-browser application, wherein displaying the associated browser tab within the user interface of the non-browser application includes displaying the associated browser tab embedded in the non-browser application.

This invention discloses an offline task scheduling method that maximizes resource utilization, belonging to the fields of cloud computing applications, computer technology, and green computing. Addressing the shortcomings of current methods such as low resource utilization and the fact that scheduling processes only consider current resource usage without incorporating future resource needs, this invention proposes a method for maximizing resource utilization in offline task scheduling. It employs a resource prediction method, considering future resource waste at the current scheduling point in time, and appropriately increases the predicted resource demand value through a feasibility index, thereby improving the future success rate of scheduled tasks. Heuristic and search pruning methods are used to reduce the number of searches when searching a large number of server states, reaching the search target faster. By setting termination conditions, this method can output scheduling results more quickly and ensure the quality of the results. This method is particularly suitable for scheduling offline tasks to clusters with existing online tasks.

Some embodiments are directed to a regulatory compliance tool implemented via a back-end application computer server. A location based regulatory compliance data store may contain electronic records associated with a set of locations. Each electronic record may include, for example, an electronic record identifier and at least one regulatory compliance parameter. The computer server may receive, from a user via an interactive graphical user interface display, a set of task indications associated with regulatory compliance. The computer server may also receive, from the user, a selected location from a set of potential locations. The computer server may then retrieve, from the location based regulatory compliance data store, information about the at least one regulatory compliance parameter associated with the selected location. The computer server may then update the display based on the retrieved information about the at least one regulatory compliance parameter associated with the selected location.

A method is disclosed. The method includes determining, by a delegated certificate authority computer, a tier from a plurality of tiers for a digital wallet provider based on a list of qualifying criteria. The method also includes generating a digital certificate based on the tier, where the digital certificate is used by a digital wallet application computer associated with the digital wallet provider to complete interactions using a digital currency maintained by a blockchain network. The method further includes transmitting, by the delegated certificate authority computer to a digital wallet application computer, the digital certificate.

A back-end application computer server may receive a request along with a descriptive term. A look-up process may be performed based on the descriptive term (and hidden terms) may establish a set of potential pre-determined descriptions. The user may select one of the potential descriptions, and a user identifier may be associated with the request. A series of dynamic information exchanges may then help assign a category to the user identifier. A partial set of initial request details may be received from a third-party device and the user may adjust and / or add details to create a complete set. A potential value may then be calculated for the request. An indication of the potential value may be transmitted to the user, and information about the user identifier may be transmitted to a user response terminal to facilitate communication between the user response terminal and the user.

A cloud migration framework may include an enterprise application data store that contains electronic records associated with enterprise applications. Each record may include, for example, an electronic record identifier and enterprise application parameters. A data repository stores a catalogue of cloud computing patterns. A back-end application computer server retrieves information from the enterprise application data store and, based on enterprise application parameters, creates a move group representing a subset of the enterprise applications. For each application in the move group, the computer server identifies whether an appropriate cloud computing pattern exists in the catalogue. If an appropriate cloud computing pattern is identified, it is used to automatically create a reference implementation of the enterprise application in a cloud computing environment. If no appropriate cloud computing pattern is identified, a pattern on-boarding process may be initiated to add a new cloud computing pattern to the catalogue.

A back-end application computer server may access a location data store containing information about a set of locations to be visited, including location identifiers and location coordinates. The computer server may then prioritize the locations to be visited. A mobile unit data store may contain information about a set of mobile units, including mobile unit identifiers, mobile unit location coordinates, and mobile unit communication addresses. The computer server may then automatically assign each location to a mobile unit based on the location coordinates, the mobile unit location coordinates, at least one geo-fence, and the prioritization. Indications of assigned locations may be transmitted to each mobile unit via the associated mobile unit communication address, and electronic messages may be exchanged to support an interactive user interface display associated with assignments of locations to mobile units. According to some embodiments, the back-end computer server facilitates collection of location information from mobile devices.

According to some embodiments, systems and methods are provided including a computer processor; and a computer memory, coupled to the computer processor, storing instructions that, when executed by the computer processor, cause the back-end application computer server to: receive an absence planning request from a first user; receive data for the first user from the data store and at least one of a first third-party platform and a second third-party platform; extract data from the received data for the first user; apply an absence planning algorithm to the extracted data to dynamically generate an absence plan; and output the generated absence plan; and a communication port coupled to the back-end application computer server to facilitate a transmission of data with remote user devices to support interactive user interface displays, including the absence plan, via a distributed communication network. Numerous other aspects are provided.

Computer-implemented methods and systems for integrating computer applications are disclosed. One method includes querying a primary computer application for current state of a newly created object; receiving the current state of the object, and generating object data for a secondary computer application based on the current state of the object. The method further includes communicating an object creation request to a secondary computer application, the object creation request including the generated object data, receiving a secondary computer application object identifier from the secondary computer application upon creation of the object at the secondary computer application, and communicating the secondary computer application object identifier to the primary computer application for storing in a record of the object created at the primary computer application.

A cloud migration framework may include an enterprise application data store that contains electronic records associated with enterprise applications. Each record may include, for example, an electronic record identifier and enterprise application parameters. A data repository stores a catalogue of cloud computing patterns. A back-end application computer server retrieves information from the enterprise application data store and, based on enterprise application parameters, creates a move group representing a subset of the enterprise applications. For each application in the move group, the computer server identifies whether an appropriate cloud computing pattern exists in the catalogue. If an appropriate cloud computing pattern is identified, it is used to automatically create a reference implementation of the enterprise application in a cloud computing environment. If no appropriate cloud computing pattern is identified, a pattern on-boarding process may be initiated to add a new cloud computing pattern to the catalogue.

The application relates to the technical field of deep learning, in particular to a UAV viewpoint optimization method, application, computer system and readable storage medium. By constructing a time sequence state space which fuses the spatial domain and frequency domain features of a leaf image and UAV parameters, a viewpoint decision action containing pose and focal length changes is generated, and a proximal policy optimization algorithm is combined with a behavior cloning training method, so that the UAV autonomously searches and locks an optimal viewpoint without occlusion and with consistent scales in a complex occlusion environment, high-quality leaf images are acquired to realize accurate pest and disease identification. The application aims to solve the problem of how to make the UAV autonomously optimize the observation viewpoint according to the leaf occlusion and image scale changes in the multi-layer leaf crop inspection process.

According to some embodiments, systems and methods are provided including a computer processor; and a computer memory, coupled to the computer processor, storing instructions that, when executed by the computer processor, cause the back-end application computer server to: receive an absence planning request from a first user; receive data for the first user from the data store and at least one of a first third-party platform and a second third-party platform; extract data from the received data for the first user; apply an absence planning algorithm to the extracted data to dynamically generate an absence plan; and output the generated absence plan; and a communication port coupled to the back-end application computer server to facilitate a transmission of data with remote user devices to support interactive user interface displays, including the absence plan, via a distributed communication network. Numerous other aspects are provided.

The invention relates to the technical field of human-computer interaction, in particular to a method for optimizing human-computer interaction interface navigation by applying a computer vision technology, which comprises the following steps: collecting user interaction data in real time through the computer vision technology and analyzing historical interaction data; constructing a cognitive map of each interface element based on an analysis result of the historical interaction data and the current interface layout; identifying key decision points and non-key areas in the cognitive map to adjust visual characteristics of each interface element; calculating cognitive loads of the user interaction paths based on the cognitive map and the user interaction data to generate a priority list of known user interaction paths; and adjusting the interface layout according to the current navigation time consumption and the cognitive load of the user interaction path in progress. According to the method, the interface layout is adjusted by matching the real-time and historical interaction paths of the user and combining the consumed time and the cognitive load, so that the requirements can be responded in real time, the navigation difficulty is timely intervened and reduced, and the interaction fluency and pertinence are improved.

Computer technology is disclosed that applies innovative data processing and visualization techniques to large multi-parameter data sets such as cellular gene expression data to find new relationships such as relationships between cells and genes and create new associative data structures within the data sets that represent these relationships. For example, scatterplots of gene expression data can be iteratively pivoted between a cell view and a gene view to find cell populations and gene sets of interest to a user.

An analytic chart data store may contain an enterprise information data structure, based on a result set received from a back-end application computer server, and a user selectable dimension ungrouping indication. The enterprise information data structure may include: an outermost dimension arranged on a row axis; an innermost dimension arranged on the row axis; and measure values arranged on the row axis. A computer processor of an analytic chart creation platform may determine that the user selectable dimension ungrouping indication is set to “ungroup.” Responsive to said determination, the analytic chart creation platform may automatically re-organize the enterprise information structure such that the innermost dimension information is arranged on the column axis instead of the row axis. The analytic chart creation platform may then automatically create an analytic chart and transmit the chart to a remote user device.

Embodiments may monitor utilization of a machine. A risk relationship data store may contain electronic records that represent a plurality of risk relationships with an enterprise. A device located proximate to the machine includes a plurality of sensors, each sensor configured to monitor at least one parameter (e.g., acceleration, speed, mileage, run-time and location sensors, etc.). A back-end application computer server may calculate an operator behavior score and a machine operation score based on sensor signals. The computer server may also determine a machine characteristics score and an amount of utilization associated with the machine. A risk relationship identifier associated with the machine is identified, and the computer server may automatically and dynamically update a resource amount associated with the risk relationship identifier based on the operator behavior score, the machine operation score, the machine characteristics score, and the amount of utilization associated with the machine.