181 results about "Automated method" patented technology

The invention discloses a cross-channel marketing automation method and system based on real-time behavior triggering. The method comprises the following steps: capturing a user behavior event flow in real time through a front-end acquisition unit; performing real-time mode matching on the event stream by utilizing a complex event processing engine, and generating a marketing trigger signal when a preset rule is matched; dynamically selecting an optimal channel for the user based on a real-time scoring model in response to the signal; the marketing content is sent to the selected channel through the unified execution module; and finally, tracking user feedback and updating model parameters and user preferences in real time to form closed-loop optimization. The corresponding system comprises a front-end data acquisition module, a streaming event processing module, a real-time intelligent decision-making module, a multi-channel execution module and a closed-loop optimization module which are used for implementing the steps. According to the method, millisecond-level intention perception, cost and experience optimal channel intelligent decision and data-driven adaptive optimization closed loop are realized, and the problems of delayed response, extensive channel and lack of self-adaption of traditional marketing are solved.

An automated method is provided for comparing a source database and a target database that are intended to be kept in synchronization with each other. An application processes transactions that are posted to the source database, and a synchronization process processes transactions that are posted to the target database. Change log data is chunked from a change log associated with the source database to create first chunks of change log data. Change log data is also chunked from a change log associated with the target database to create second chunks of change log data. A comparison engine compares representations of the first chunks of change log data with representations of the second chunks of change log data, wherein the second chunks of change log data correspond to the same respective first chunks of change log data that were made to the source database and kept in synchronization with the target database via the synchronization process. The source database and the target database are presumed to be in synchronization with each other via the synchronization process when the comparison indicates that the representations of the first chunks of change log data match the representations of the second chunks of change log data. The source database and the target database are presumed not to be in synchronization with each other when the comparison indicates that the representations of the first chunks of change log data do not match the representations of the second chunks of change log data. An action is performed when the comparison indicates that the representations of the first chunks of change log data do not match the representations of the second chunks of change log data. The action may be a corrective action that resynchronizes the target database with the source database, or that suspends or stops the application from processing transactions.

The invention discloses an automatic tightening method for vehicle screws, and relates to the technical field of automatic control, and the method comprises the steps: obtaining the dynamic information of a target vehicle and the initial position information of all target screw holes; based on the dynamic information, the mobile platform is controlled to perform synchronous following motion, so that the mobile platform and the target vehicle keep a preset relative position relationship; based on the initial position information, an execution mechanism installed on the mobile platform is controlled to position a preset target screw hole, the actual position of the preset target screw hole is obtained, and the preset target screw hole is determined from all the target screw holes based on a preset screening rule; determining target positions of all target screw holes based on the actual position and initial position information of the preset target screw holes; and the execution mechanism is controlled to move to target positions corresponding to all the target screw holes, and all the target screws are tightened.

The invention discloses a method for automatically constructing a pathological image data set and training cell nucleus detection and classification based on a space transcriptome technology, and belongs to the field of image processing and artificial intelligence auxiliary pathological diagnosis. According to the method, a spatial transcriptome public data set is obtained, and a data set containing image blocks, weak supervision / semi-supervision labels and cell nucleus boundary information is automatically constructed through preprocessing, deconvolution cell type annotation and cell nucleus instance segmentation, so that the dependence on manual annotation is reduced. Furthermore, a detection and classification model is designed, a multi-scale deformable attention encoder and a decoupled detection and classification decoder are adopted, a limited deformable cross attention mechanism is introduced into the classification decoder, KL divergence classification loss is combined, and instance-level cell nucleus categories are learned from region-level proportion labels. According to the method, end-to-end automation is realized, the cell nucleus detection and classification precision and efficiency are improved, and a high-quality pre-training model basis is provided for downstream pathological analysis.

The invention relates to the technical field of road construction automation and intelligent control, discloses an intelligent sensing and control road laying automation method and system, and aims to solve the problem of unstable construction quality caused by discontinuous sensing data, poor equipment collaboration and lack of closed-loop feedback in the prior art. The method comprises the steps that operation parameters and material state data of paving and compacting equipment are collected in real time through a multi-mode sensing module; performing space-time alignment and fusion on the multi-source heterogeneous data, and constructing a high-precision three-dimensional digital construction model; and on the basis of a model prediction control algorithm, combining the laying quality prediction model and multi-objective optimization to generate optimal equipment control parameters. According to the scheme, intelligent sensing, self-adaptive decision making and accurate control in the construction process are achieved, the pavement flatness, the compaction uniformity and the construction efficiency are remarkably improved, manual dependence and resource waste are reduced, and the construction safety and the engineering quality traceability are enhanced.

The invention provides an automatic detection method and system for in-situ purity data of a radiopharmaceutical separation device, and relates to the technical field of data processing.The method comprises the steps that in-situ purity data is divided into a plurality of turning fragments, the anchoring offset relation of all nodes relative to a front anchor point and a rear anchor point is identified, and an anchoring sequence is constructed; calculating a response difference value and a time compression amount of adjacent nodes in each anchoring sequence, identifying a structure offset degree of a local signal in a turning segment, obtaining a bit segment extrusion amount, carrying out proportional reflection trimming on each node in the anchoring sequence, constructing a reflection node sequence, extracting a tail end reflection node and a starting reflection node of the adjacent turning segment, and obtaining a reflection node sequence; and identifying the evolution trend of the overall purity change to obtain the purity migration amount, and detecting the in-situ purity data to obtain in-situ purity detection data. According to the invention, timely and accurate purity monitoring can be realized in the separation device.

The invention relates to the technical field of software engineering automation of digital data processing, and discloses a game development automation method based on a multi-agent system. The method is used for solving the problem that a machine-readable cross-product dependence model and consistency verification are lacked in a traditional method. According to the method, based on a task list freezing project context, a constraint packet and a threshold aperture, and based on a demand account book and registration demands, constraints, codes, configuration, resources and other entry abstracts, version information and strong and weak reference relationships; the multiple agents only submit change packets in a temporary storage area by writing tokens and occupying fragmentation write-in gating, and an influence range report binding verification list is generated for each change packet; boundary compliance, reference integrity, compilation verification, determinacy operation verification and acceptance assertion verification are sequentially carried out on the temporary storage area snapshots, and when conflicts occur, rollback or confinement repair is triggered to output traceable and acceptance deliverables based on reproducible evidence judgment.

Globally our environment comprises structures built to perform a meet different requirements including residential, commercial, retail, recreational and service infrastructure. Whilst millions of tons of construction materials are deployed annually the quality control procedures in many instances have not changed to reflect today's demands. Accordingly, it would be beneficial to provide construction companies, engineering companies, infrastructure owners, regulators, etc. with means to automated testing / characterization of construction materials during at least one of its manufacture, deployment in construction and subsequent infrastructure life. It would be further beneficial for such automated methods to exploit self-contained data acquisition / logging modules allowing them to be employed with ease at the different points in the life cycle of a construction material and / or construction project.

Systems and methods are disclosed for automated method parameter configuration for differential mobility separations. As non-limiting examples, various aspects of this disclosure provide receiving a sample in an open port interface; transferring the sample to an ionization source; ionizing the transferred sample; introducing the ionized sample into a mass spectrometer; mass analyzing the ionized sample to produce an initial mass analysis result; determining a peak width of the initial mass analysis result; and determining a dwell time for subsequent measurements based on the determined peak width, a pre-defined number of data points across subsequent mass analysis peak widths, and a number of different analytes to be assessed for the sample. The sample may be diluted and transferred to the ionization source by a sample introduction apparatus selected from a group including an acoustic droplet ejector (ADE), a pneumatic ejector, a piezoelectric ejector, and a hydraulic ejector.

The invention discloses an automatic advertisement screenshot and container automatic expansion method and system in a virtual desktop environment. A virtual display capable of exporting a DMA-BUF is created by deploying a Virtual Display Driver in a kernel of a host machine, and after Chrome is driven by Puppeteer to complete hardware acceleration rendering in a container, zero-copy desktop-level screenshot is carried out on a shared memory frame buffer by utilizing desktop-script-native; and meanwhile, a Kubernetes CRD unified database task and a declarative API are adopted, a Redis Stream second-level index and a predictive HPA algorithm are combined to realize advanced delta t capacity expansion of Pod, and the P99 queuing delay is ensured to be less than 2s. According to the method, single-node concurrency is improved by 3.2 times without extra hardware cost, CPU occupation is reduced by 45%, WebGL / Flash advertisement fidelity is 100%, and the method is suitable for cloud advertisement verification, brand security and programmed creative monitoring scenes.

The invention provides an automatic front-end rendering defect repairing method and related equipment, and the method comprises the steps: determining a key event in a front-end application, and determining at least one burying point assembly corresponding to the key event; performing point burying on the point burying component, and obtaining a point burying log generated by the point burying component when the key event occurs; based on the point burying log, detecting whether a preset problem and a corresponding problem type exist in a front-end page, and when the problem is detected, generating problem information containing the problem type and corresponding path information; based on the path information, obtaining a code file corresponding to the question type; aggregating the problem information, the burying point log and the code file, performing analysis and reasoning through a preset large language model, retrieving a code problem based on the problem type, and generating an optimization code; and deploying the optimization code to a preset environment. According to the invention, the automatic repair efficiency of the front-end rendering defect is greatly improved.

A computer-implemented method includes presenting a user interface to a user, upon receiving an input from the user, presenting a beginning user interface to the user, receiving customer information through the user interface, providing directions to the user for gathering information and photos about one or more spaces for a construction project, providing prompts to the user and receiving information including at least a type of construction project, sending the photos and information about the construction project to a fine-tuned large language model (LLM), using the fine-tuned LLM to select relevant elements from the photos and information, and produce one or more data objects, receiving the data objects from the LLM and converting the data objects to one or more construction estimates, the construction estimate including at least a labor estimate, and presenting the construction estimate through the user interface to the user.

Embodiments presented provide for processing of sonic images. In specific embodiments, an automated method for separation of upper and lower reflector signals is presented.

The invention relates to the field of seismology, signal processing and artificial intelligence, namely to automated methods and systems for early detection of earthquakes based on the analysis of seismic data, and can be used to recognize and classify longitudinal waves (P-waves) preceding the main seismic shocks, using deep learning and computer vision methods. The aim of the present invention is to create an automated early earthquake detection system using the classification of seismic signal spectrograms generated by the complex Morlet wave CWT using the YOLO deep neural network architecture. The technical result is an increase in the accuracy and speed of early earthquake detection by analyzing the time-frequency characteristics of seismic signals and automatically localizing P-wave signatures using a neural network model. The device includes a seismic sensor, an analog-to-digital converter, and a microprocessor implementing time-frequency analysis and neural network detection algorithms. The seismic signal is recorded in real time, digitized, segmented into time intervals, and subjected to preliminary digital processing, including noise filtering and amplitude normalization. Each time interval is converted into a time-frequency representation using a continuous wavelet transform, generating a two-dimensional distribution of signal energy over time and frequency. Based on the obtained data, a spectrogram is generated and fed to the YOLO neural network detection model, which is capable of automatically detecting and localizing longitudinal P-wave signatures. Based on the neural network analysis, a determination is made regarding the presence of a P-wave and its arrival time is determined. If a predetermined threshold is exceeded, an early warning signal is generated. The system provides for data accumulation and the possibility of subsequent retraining of the neural network model.

The current document is directed to methods and systems that provide an emotional compass that reflects the emotional states of human beings, dynamics of the emotional states over time periods, emotional synchronization between humans and between humans and automated interactive systems, and the degree to which the emotional state of one human is influenced or affected by the emotional state of another human or by an automated interactive system. The emotional compass can be used for continuous or intermittent emotional orientation by both automated systems and human analysts. The emotional awareness provided by the emotional compass facilitates continuous or intermittent strategy selection for achieving various different types of emotion-related results.

This application belongs to the field of nondestructive testing technology, specifically relating to an automated method and device for wet magnetic particle inspection and identification of weld areas in drill pipes, aiming to solve the problem of insufficient automation in weld area inspection and identification of drill pipes. This application includes: acquiring magnetic trace images of the surface of the weld area of ​​the drill pipe; processing the magnetic trace images based on a preset image analysis model to identify abnormal regions in the magnetic trace images; comparing the abnormal regions with pre-established defect feature information to determine whether the abnormal regions are defective regions; if the abnormal regions are determined to be defective regions, obtaining the spatial coordinates of the defective regions in the drill pipe cylindrical surface coordinate system based on the position of the defective regions in the image coordinate system; and controlling the rotation of the drill pipe based on the spatial coordinates to position the defective regions at a marking station for automatic marking. This ensures the stability and reliability of the inspection quality, effectively avoids missed detections and false judgments, and solves the problem of insufficient automation in existing equipment.

The invention relates to an automated method for data-based error cause analysis for at least one deviation in a container treatment process in a container treatment machine of the beverage / filling industry from a target container treatment process. The method comprises: determining at least one deviation in a container treatment process in a container treatment machine of the beverage / filling industry from a target container treatment process by analysing sensor data and / or measurement data from sensors and / or measuring devices provided in the container treatment machine; bringing the determined at least one deviation into context with a most probable error cause; outputting the most probable error cause for an error which causes the at least one deviation and an action instruction for rectifying the error; and applying the action instruction to rectify the error.

Automated methods may comprise automatically converting a ballistic trajectory of a projectile into a ballistic flight path. The ballistic flight path may comprise one or more segments. Each of the segments may comprise a plurality of coordinates. The coordinates may be located along the ballistic trajectory. The automated method may comprise automatically navigating an Unmanned Aerial Vehicle (UAV) along the ballistic flight path. The automated method may comprise automatically collecting environmental data along the ballistic flight path through employment of the UAV.

Rodeo and / or equestrian event competition timing systems and associated devices and methods are disclosed. The competition may be an equestrian or rodeo event, including livestock riding and roping including break-away roping. Methods, devices and systems for timing such events are provided. Methods replacing manual and human-eye based event timing for at least one of event starting, event stopping, or both, with automated methods are explained.

Methods of designing a 3D Integrated Circuit including: partitioning at least one design into at least two levels, a first level and a second level, where the first level includes first transistors, where the second level includes second transistors is on top of the first level; providing placement data of the second level; performing a placement of the first level using a placer program executed by a computer, where the placement of the first level is based on the placement data, where the placer is part of a Computer Aided Design (CAD) tool, and where the first level includes first routing layers; performing a routing of the first level using a router {part of the CAD tool or another CAD tool) executed by a computer, where at least one metal routing layer is disposed in-between the first transistors and the second transistors, and the second level includes repeating structures.

This application provides an automated method for generating road crack segmentation networks based on neural architecture search. The method first constructs a customized neural architecture search space for crack segmentation tasks. Then, it employs an efficient search strategy to automatically generate a diverse and efficient set of candidate network architectures by comprehensively evaluating the differences in structural distance, computational cost, and operator sequences. Next, a composite loss function is used during training to address the sample imbalance problem, and a multi-objective function considering both accuracy and efficiency is used for evaluation. Finally, the optimal architecture is automatically selected, and training and testing are completed. This method significantly reduces the computational cost of neural architecture search and can automatically and efficiently generate lightweight crack segmentation networks with both high segmentation accuracy and low computational complexity. It effectively solves the technical challenges of existing manual design methods that rely on experience, and the high cost and poor task adaptability of general automated methods.

The invention discloses a graphical code verification method, and relates to the technical field of rail transit signal systems, and the method comprises the following steps: S1, reading a new version demand document FS, a design document AD and a graphical code EMIL of a subsystem; s2, comparing the demand document FS and the design document AD of the new version and the old version, and associating to obtain an NEWTrace table file and an OLDTrace table file; s3, the NEWTrace table file and the OLDTrace table file are traversed, and a ChangeLog table is obtained; s4, reading a new and old version graphical code EMIL and a ChangeLog table, and generating a code comparison text file and an AD check text file; s5, traversing and updating the Themes verification table; s6, verifying the consistency of the requirement for modifying the entry and the code; and S7, summarizing all verification results of the Themes verification table. According to the method, demand design and codes are integrated, corresponding modification demands and modification codes are identified and triggered through an automatic method, walking verification is facilitated, and the code walking verification efficiency is improved.

An automated method for aligning a 3D single tooth model to 3D oral scan data includes determining an oral scan landmark and a teeth curve formed by teeth in the 3D oral scan data, determining a margin line of a target tooth in the 3D oral scan data and a region of interest in the 3D oral scan data, determining first to third axes of the 3D oral scan data in the region of interest based on the oral scan landmark, determining a single tooth landmark of the 3D single tooth model, determining fourth to sixth axes of the 3D single tooth model based on the single tooth landmark and aligning the 3D single tooth model to the 3D oral scan data such that the fourth to sixth axes of the 3D single tooth model respectively overlap the first to third axes of the 3D oral scan data.

The invention relates to an automatic method for dynamically adjusting compressed air, which belongs to the technical field of compressed air process, and comprises the following steps: S1, an automatic model acquires process consumption, output flow, equipment operation state and equipment number; s2, inputting the artificial experience of the use amount change into the automatic model; and S3, the automatic model performs automatic control on the equipment according to the equipment number sequence and the collected and input signals. According to the invention, the systematized adjustment capability of compressed air can be realized, the pressure of a pipe network and the relationship between the use amount and the generation amount of a user are dynamically balanced, and the purposes of energy conservation and consumption reduction are realized.

The present application belongs to the field of computer vision and medical image processing, and particularly relates to a multi-view bladder volume measurement method based on improved YOLO detection and positioning. The method comprises the following steps: step 1, pre-processing of bladder ultrasound image data; step 2, establishing a joint neural network model for view classification and bladder positioning; step 3, detection of bladder ultrasound image cross-section and longitudinal section; step 4, scale detection; and step 5, bladder volume calculation and correction. The present application realizes an automatic method integrating multi-view ultrasound image recognition and bladder volume measurement, so as to reduce the dependence on professional prior knowledge and lower the operation threshold of non-professional doctors; at the same time, the method can provide relatively objective diagnostic reference data under different equipment environments and image qualities, and improve the scientificity of auxiliary medical decision-making.

The present invention generally relates to the field of taxonomy identification. Identifying product taxonomy from a product abbreviation is currently performed manually and consumes lot of time and effort. Hence, embodiments of present disclosure provide an automated method for identification of product taxonomy from product abbreviation. First, a brand name of product abbreviation is predicted using a Large Language Model (LLM) and a brand list. Then, possible expansions of the abbreviation are generated based on the brand name using acronym expansion dictionary. Among the generated possible expansions, a relevant one is identified using the LLM. Later, web scraping and web search techniques are applied on the relevant expansion to obtain associated top k matches of a supergroup, a product group and module of the predicted relevant expansion. Finally, product taxonomy is predicted based on the top k matches using a LLM augmented taxonomy classification by Retrieval Augmented Generation.

Various embodiments of the teachings herein include an automated method for data access to a device by an external client, allowing the device to communicate with an internal communication network while the external client communicates with an external communication network. An example method includes: sending a communication access request from the external client for the device to a software implemented application access point; configuring a corresponding software implemented connector using the application access point, so the connector acts as an endpoint for a communication tunnel to the device; configuring a corresponding software implemented policy decision point using the application access point as an interface to the external network for arriving of application data traffic of the external client, so the policy decision point is set up to validate, accept, and forward the access request of the external client to the connector; and accessing the device via the communication tunnel.