10results about How to "Automatic collection" patented technology

The invention provides a group epigenetic analysis method and system based on consensus peak recognition, and belongs to the technical field of bioinformatics, and the method comprises the steps: S1, recognizing a consensus peak from a multi-sample peak file based on a position offset threshold and a minimum sample proportion; s2, calculating the coverage depth of a consensus peak based on the segment / read segment to obtain an original peak intensity matrix; s3, eliminating GC preference through GC content inter-partition local correction; s4, performing cross-sample normalization by adopting methods such as DESeq2, TMM and the like; and S5, automatically removing a hidden batch effect by utilizing potential variable analysis. The system correspondingly comprises five functional modules. According to the method, the problems of inconsistent peak coordinates, incomparable signals and large technical deviation interference in multi-sample epigenetic data are solved through an integrated process, full-automatic generation from original data to a high-quality and high-comparability peak intensity matrix is realized, and the analysis efficiency and accuracy of researches on large-scale groups ChIP-seq, ATAC-seq and the like are remarkably improved.

This utility model discloses a mouse rewarming device, comprising: a resuscitation and rewarming unit, including multiple layers of rewarming components for rewarming multiple groups of mice, and a transfer component located on one side of the outlet of the rewarming components for transferring mice out of the rewarming components after rewarming and resuscitation; and a collection unit located at the outlet of the transfer components for accommodating mice that have escaped from the transfer components. The collection unit has multiple layers corresponding to the rewarming components. By placing mice requiring rewarming and rewarming within the rewarming components, with each group of mice placed in a corresponding layer within the rewarming components, the mice, after waking up, will move from the rewarming components to the transfer components, and then from the transfer components into the collection unit. This ensures that the layer in which the mice enter the collection unit is the same as the corresponding layer in the rewarming components, thereby automatically collecting the revived mice and preventing confusion between the collected groups of mice.

This invention relates to the field of intelligent management technology, specifically to a method and system for intelligent management of flight attendants based on multimodal data fusion. The method first collects multimodal time-series data of flight attendants, including physiological signals, operational behaviors, computer vision, and environmental data, through a sensor network deployed in the flight attendant environment. Next, it uses a deep learning model that integrates a time-series model, convolutional networks, and attention mechanisms to comprehensively analyze the data and dynamically predict health risk indices and operational behavior compliance scores. Then, based on the prediction results, it triggers tiered health risk warnings and real-time operational behavior guidance. Finally, combining the prediction results with operational needs, it uses a reinforcement learning model for adaptive and optimized shift scheduling. This invention achieves continuous and accurate perception of flight attendant status, proactive risk warnings, real-time behavioral correction, and dynamic optimization of human resources, forming an intelligent closed-loop management system that significantly improves safety management and operational scheduling efficiency.

The invention discloses an acceleration acquisition method and device based on a vehicle dynamics attention network. The method comprises the steps of 1, collecting vehicle parameters; 2, training vehicle parameters by adopting a vehicle dynamics attention network: carrying out feature extraction on a 5-dimensional vector, and mapping the 5-dimensional vector into a 20-dimensional vector space; serializing the dimension and expanding the dimension to generate multi-head attention; carrying out residual error connection and normalization; flattening the 32-dimensional vector space to a 20-dimensional vector space by using a feed-forward layer neural network; carrying out residual error connection and normalization again; after pooling, outputting a scalar of the predicted acceleration; and 3, calculating the total loss according to the constraint loss function of the kinetic model of the vehicle. The device comprises an input interface module, a storage module, a processor for executing vehicle dynamics attention network training and an output interface module. According to the method, the vehicle dynamics attention network is adopted, data driving and physical modeling are combined, and the generalization ability and physical consistency of the model are remarkably improved.

This invention discloses an enterprise procurement supply chain collaborative management system, comprising: a perception layer deployed at each node of the procurement supply chain, used to collect data on the flow and processing of renewable resource materials through passive RFID tags built into heterogeneous devices, and to perform data verification and synchronization through an inter-device self-organizing network; a trust layer used to bind the operator's biometric information with their identity, operating permissions, and initial credit rating, and to dynamically manage credit and cross-enterprise permissions based on their operating behavior and device feedback; and an analysis and decision-making layer used to analyze and issue early warnings on the perceived data through an edge computing module, and to simulate the value transformation path under different working conditions through a virtual mapping model. By deploying computing modules at the network edge, this invention can process data locally, independently and quickly identify and issue early warnings for anomalies such as equipment failures and quality deviations, achieving a leap from post-event response to pre-event prediction and in-event intervention.

This invention relates to the field of agricultural machinery technology, and more particularly to an agricultural mulching device; it includes a frame, a film roller, a film opening mechanism, and a soil covering mechanism. By setting an identification module on the soil covering mechanism, the width and edge of the film can be detected in real time, and the controller automatically adjusts the distance between the two film-pressing and feeding pipes on the bidirectional lead screw, ensuring that the soil covering position is always accurately aligned with the film edge, adapting to mulch films of different widths without manual intervention. The film opening mechanism of this application adopts a horizontally movable and vertically adjustable hot-pressing opening method, and is equipped with negative pressure suction to recover waste materials. This not only ensures smooth opening edges without tearing the mulch film, but also automatically collects waste materials, avoiding residual pollution in the field. The soil-collecting and conveying mechanism of this application uses an angle-adjustable feeding auger, which can flexibly adjust the soil-collecting angle according to ground conditions and soil covering requirements, directly collecting and conveying soil to the hopper, and then quantitatively covering the soil through the film-pressing and feeding pipes. The structure is compact and the operation is highly continuous.

The utility model discloses a sewage sampling and collecting device in the sewage treatment process, which comprises a movable cart, a telescopic sampling structure is connected to the end face of the movable cart, and a rotary collecting structure is connected to the end face of the movable cart and located on one side of the telescopic sampling structure. According to the sewage sampling and collecting device, the telescopic sampling structure is arranged in the sewage sampling and collecting device in the sewage treatment process, so that a driving motor in the telescopic sampling structure passes through the transmission structure, and the telescopic sampling structure is connected with a controller through the transmission structure; according to the sewage sampling device, the sampling guide pipe at the tail end of the scissor type telescopic frame can extend to the sampling depth according to the requirements of the sampling depth during sewage sampling, so that sewage sampling is more convenient, the water taking depth is more accurately controlled during sewage sampling, and data acquired by sewage is more accurate.

The invention provides a large overflow discharge port pollution load capacity calculation method and system, and the method comprises the steps: deploying a robust multi-mode sensing array with a self-cleaning function and / or a redundancy calibration function in an overflow discharge port, and optimizing the layout position to obtain real-time synchronous flow and pollutant concentration data with high representativeness; a graded variable-frequency dynamic acquisition strategy is adopted, different sampling frequencies are adapted according to hydraulic and water quality characteristics of different overflow stages, and data precision and energy consumption control are both considered; dividing a normal period and an overflow period based on the flow data, respectively calculating pollution load of each stage by adopting a time weighted average method and a real-time integral method, and accumulating to obtain the annual total amount; regular standard solution calibration and laboratory data verification are matched, and the result accuracy is further guaranteed. According to the method, dependence on theoretical model parameters is eliminated, the precision and reliability of pollution load calculation are remarkably improved, the adaptability of system modular design is high, the operation and maintenance cost is low, and data support is provided for drainage basin water environment management, sewage right verification and the like.

This invention provides a laser rangefinder sensor fixing device and installation method for a dynamic compaction machine, belonging to the field of civil engineering monitoring technology. The device includes: a fixing mechanism for connecting the entire device to the boom of the dynamic compaction machine; a vibration damping mechanism mounted on the fixing mechanism for isolating the impact vibration of the dynamic compaction; and a steering mechanism mounted on the vibration damping mechanism for adjusting the attitude of the laser rangefinder sensor. The laser rangefinder sensor of this invention achieves angle adjustment through the steering mechanism, is mounted on the boom of the dynamic compaction machine through the fixing mechanism, and is isolated from the impact vibration of the dynamic compaction through the vibration damping mechanism, ensuring the accuracy and stability of the laser rangefinder sensor's distance measurement. This device is recyclable; after the completion of a single construction project, the device can be safely, conveniently, and completely disassembled and recycled, and directly used in subsequent projects.

The application discloses a waste cleaning temperature controller electrode sheet production stamping forming equipment, and relates to the technical field of temperature controller electrode sheet production. The application discloses a waste cleaning temperature controller electrode sheet production stamping forming equipment, and relates to the technical field of temperature controller electrode sheet production. The application discloses a waste cleaning temperature controller electrode sheet production stamping forming equipment, and relates to the technical field of temperature controller electrode sheet production.