240results about How to "Simplify the build process" patented technology

The invention discloses a 6D pose estimation method and system based on an RGBD camera, and relates to the technical field of computer vision processing. Calibrating camera parameters based on the calibrated camera imaging; reconstructing a three-dimensional model and constructing a data set; segmenting the target object and calculating the actual size based on the three-dimensional model and the data set; establishing a 6D pose estimation network model based on the three-dimensional model and the data set; and performing pose estimation based on the actual size. The method has the advantages that the accuracy of 6D pose estimation is remarkably improved by combining the RGB image, the depth image and the point cloud data, object region segmentation is performed by using the SAM model, the actual size of the object is visually calculated by combining the depth information and the point cloud data, the precision of size estimation is improved, and the method is suitable for popularization and application. The introduction of depth information enables the pose estimation system to have better adaptability to objects with different sizes, shapes and surface features, and improves the robustness and accuracy of the system.

The embodiment of the invention discloses a three-dimensional reconstruction method based on structured three-dimensional Gaussian representation. The method comprises the following steps: acquiring a target image containing a target object at multiple visual angles; generating an unstructured Gaussian primitive representation corresponding to the target object according to the target image; establishing a transmission matrix describing the unstructured Gaussian primitive distribution and the structured Gaussian primitive distribution, solving the transmission matrix by using an optimal transmission algorithm, and generating a structured Gaussian primitive representation corresponding to the target object according to the optimal transmission matrix; obtaining a text description for the target object, and complementing the structured Gaussian primitives according to the text description by using a diffusion model obtained by pre-training; and performing three-dimensional reconstruction by using the complete structured Gaussian primitive. According to the method, the optimal transmission algorithm is used for carrying out structured representation on the three-dimensional Gaussian primitives, and text description is used for complementing the Gaussian primitives through the diffusion model, so that the quality of three-dimensional reconstruction is improved.

The invention relates to the technical field of natural language processing, in particular to an enterprise transformation diagnosis report generation method based on a large model. Collecting corpus data by using an enterprise diagnosis questionnaire; constructing a digital transformation diagnosis knowledge base, and storing the knowledge base into a vector database; training a sample model, and constructing a diagnosis report template through fine tuning of Prompt cue words; and taking the fine-tuned cue word as input, automatically generating a diagnosis report by utilizing the trained large model, selecting different file formats by utilizing an agent, generating a diagnosis report and outputting the diagnosis report. Through questionnaires and industry characteristic analysis, diagnosis suggestions are intelligently generated, enterprise transformation pain points are identified, and the efficiency and accuracy of enterprise transformation diagnosis are improved.

The invention discloses a correction method and system for laser emission direction adjustment, and relates to the technical field of image processing, and the method comprises the steps: capturing laser spot real-time image data through a CCD camera, extracting a spot region through a U-Net model, and setting a standardized reference region through calculating the side length of a square frame; selecting light spots by using a square frame to establish a relative coordinate system, carrying out gridding processing and positioning the centers of the light spots, and finally converting the light spots into actual coordinates of a world coordinate system; acquiring reflected and transmitted light spot coordinates and light spot position data from the position sensitive detector and the optical fiber sensor, and calculating deviation by using structural projection to obtain a corrected cursor; and a processing plane network model is constructed in the laser correction server, a galvanometer rotation angle set is calculated, laser scanning is executed, and feedback and correction are performed according to the deviation between the actual light spot position and the theoretical positioning point. According to the invention, the light spot region is extracted through the U-Net model, high-precision light spot segmentation is realized under the complex background and noise interference, and the accuracy of light spot positioning is improved.

The invention provides a shale oil fracturing effect evaluation method and device, a terminal and a storage medium, and belongs to the technical field of petroleum engineering. According to the method provided by the embodiment of the invention, the fuzzy comprehensive evaluation method is utilized to perform fuzzy processing on the basic parameters such as the target reservoir parameters and the target engineering parameters, so that the values of the basic parameters are more representative and are not certain values, and therefore, an evaluation result close to the reality can be obtained, and the accuracy of a calculation result is improved; and optimizing the shale oil fracturing effect evaluation method. Moreover, by fitting the function model of the main control factors and the yield and utilizing the function model to evaluate the fracturing effect, the model construction process is simplified, and the evaluation efficiency is higher.

The invention relates to an energy-saving optimization control method and system, computer equipment and a computer readable medium. The method comprises the following steps: acquiring historical data of equipment; preprocessing the historical data; performing feature extraction on the preprocessed historical data; screening the extracted features to obtain target features representing the energy consumption of the equipment; constructing a neural network model based on the target features; performing energy consumption prediction on the equipment by using the neural network model; and regulating and controlling the equipment based on the energy consumption prediction result of the neural network model. According to the invention, the construction process can be simplified, and the prediction performance and calculation efficiency of the constructed neural network model can be improved; manual intervention can be reduced, the operation state of the equipment can be adjusted in real time according to environmental changes, energy waste can be avoided, the energy use efficiency and the regulation and control efficiency can be improved, and the optimal energy-saving effect can be achieved in time.

The invention discloses a transformer hollow winding model building method and system based on a multi-function PEEC method. The method comprises the steps that discretization processing is conducted on a target transformer winding, and the target transformer winding is divided into a plurality of volume units and area units; according to geometric parameters of the volume units and the area units, partial inductance matrixes, potential coefficient matrixes and resistance matrixes among all the grids are calculated; according to geometric characteristics of a target transformer winding, different improved approximation methods are adopted to calculate specific numerical values of the partial inductance matrix and the potential coefficient matrix; and establishing a target transformer winding equivalent circuit model according to the partial inductance matrix, the potential coefficient matrix and the resistance matrix of which the specific numerical values are calculated. The method not only improves the accuracy and calculation efficiency of the model, but also simplifies the model building process, improves the performance prediction capability of the transformer, and has high adaptability.

The invention provides a satellite phased array wave beam scanning application method, which comprises the following steps that: in a broadcast time slot, phased array transmitting wave beams cover wave positions one by one according to a scanning pattern, and when the wave positions of satellite terminals are covered, the satellite terminals receive satellite-ground announcements; the satellite terminal scans the pattern information according to the common control channel resources and the scanning pattern information in the satellite-ground announcement; carrying out random access in the common control time slot; and after the access is successful, allocating a service beam, and dynamically generating a scanning pattern of a service time slot and a time slot allocation plan during a beam position residence period according to the position information and service requirements of the satellite terminal, thereby meeting communication requirements. According to the method provided by the invention, through fine division and dynamic allocation of time slot resources and in combination with the design of a phased array scanning strategy, wide-area concurrent service, random access and on-demand coverage of a satellite to a plurality of ground terminals are realized, and efficient utilization of phased array beam resources is ensured.

The invention provides an iterative least square artificial magnetic field positioning method and device not affected by attitudes, belongs to the field of indoor positioning, and aims to solve the problem of complexity increase caused by carrier attitudes, adopts an artificial magnetic field positioning observation equation establishment method not affected by attitudes, avoids introduction of unknown quantity of attitudes in a mode of solving a model according to frequency, and improves the positioning accuracy. Establishing a simplified observation equation based on a magnetic induction intensity module value so as to reduce the number of nonlinear unknown quantities of an equation set and play a role in reducing a search space and the number of local optimal solutions for a subsequent optimization solution thought; aiming at a nonlinear equation solving problem in a position solving process, an algorithm for carrying out positioning inversion solution according to iterative least square is given, linear expansion is continuously carried out at an iteration point by taking a model of a difference between a minimum state quantity and a real-time observed quantity as a target, and iterative calculation is carried out by utilizing the least square. According to the method, global optimal and high-convergence-speed high-precision position solving is realized.

A converter station AC filter group circuit breaker abnormal arcing modeling analysis method comprises the following steps: firstly, carrying out time mark alignment, amplitude calibration and filtering de-noising on wave recording signals such as AC bus voltage and filter branch current to obtain high-quality input data; then, combining a primary wiring diagram, enabling an alternating current system to be equivalent to an ideal power supply and series impedance, enabling circuit breaker arcing to be equivalent to arc resistance changing along with time, and constructing an equivalent circuit model comprising the power supply, the impedance, a capacitor, an electric reactor and dynamic arc resistance; establishing a state space equation according to a voltage and current constraint relation, and performing time domain solution by adopting a two-step two-order or three-order diagonal implicit Runge-Kutta method to obtain voltage and current responses of the whole process of the fault; on this basis, the arc resistance change is inversed according to the ratio of arc voltage to current, the current zero passage is identified through the resistance symbol change at adjacent moments, and the zero passage section is smoothed; and finally, the inversion result is verified again by means of the simplified equivalent model.

The invention provides a construction method and application of a portable rapid visual tobacco mosaic virus paper-based molecular imprinting sensor. According to the sensor, tobacco mosaic virus (TMV) is taken as a template, high-specificity organic fluorescent nanogel imprinted polymer TMV-nanoMIPs obtained by solid-phase imprinting is taken as signal output, meanwhile, a cheap and portable paper base is taken as a sensing chip, TMV is imprinted on the paper base, and the paper-based imprinted polymer WP-coated MIPs with a TMV imprinted cavity is obtained after elution. After the WP-coated MIPs specifically capture the TMV, the TMV-nanoMIPs also can be combined to the TMV due to the specificity of the TMV-nanoMIPs, so that a sandwich structure of the MIPs-TMV-MIPs is formed. The TMV-nanoMIPs are used as the signal probe, the rapid semi-quantitative visual detection of the target virus TMV by naked eyes and an ultraviolet lamp is realized, the obvious change can be observed within ten minutes, and meanwhile, the TMV-nanoMIPs can be quantitatively detected and analyzed through a fluorospectro photometer. And the method has good detection capability in tobacco leaves actually infected by TMV, and the cost of the method is as low as 0.623 yuan / piece. The sensor is expected to realize on-site self-service rapid visual detection when crops are infected with viruses, and has important significance on prevention and control of plant diseases and pests.

The invention provides an enterprise information security automatic response method and device, and belongs to the technical field of network information security, the method comprises the following steps: firstly, outputting an alarm IP and an alarm level of an alarm log through a large language model, and then carrying out analysis through a multi-layer rechecking mechanism: if the IP geographic position of the alarm log is the Internet, further analyzing the IP threat degree; if the IP threat degree is malicious, further confirming whether the alarm IP is matched with a local white list; if the matching is unsuccessful, the IP risk level is marked as malicious, and the IP risk level is marked as suspicious under other conditions. And finally, by calculating a risk value comparison threshold value of the alarm IP, determining whether the alarm IP is malicious or not and taking a blocking measure. According to the method, the construction link of an enterprise information security operation and automatic response platform can be simplified, the discovery possibility and the automatic response capability of security personnel on unknown attack behaviors in massive logs can be increased, and the probability of information security events of enterprises is reduced.

The invention relates to a video and slide generation method, electronic equipment and a storage medium, and the method comprises the steps: responding to a received file, extracting picture information and / or table information in the file, obtaining a file type corresponding to the file through detection, processing the file based on the file type, and converting the file into a preset form; in response to the received story background and text cue word information, taking the text information subjected to form conversion as input of a large language model, and taking the story background and the text cue word information as guidance to generate a lightweight language text; and converting the obtained lightweight language text to obtain a voice file, inserting the picture information and / or table information into the obtained lightweight language text, converting the lightweight language text into a slide file, and synthesizing the voice file and the slide file to obtain a video file, thereby realizing controllable video generation. Compared with the prior art, the method has the advantages of high correlation degree of the generated video and the like.

The invention provides a quantum classical hybrid machine learning model construction system. The quantum classical hybrid machine learning model construction system comprises a data set unit, a calculation layer unit, an automatic differential unit and a model training unit. The dataset unit provides a dataset loading service, a dataset preprocessing service and a coding service which are selectable to generate a target training set. The calculation layer unit constructs an initial machine learning model based on a classic and quantum calculation layer selected or customized by a user. The automatic differentiation unit provides alternative loss function configuration service and differentiator configuration service and automatically configures a classic differentiator based on an initial machine learning model. And the model training unit provides a classic optimizer configuration service, a classic scheduler configuration service and a training method configuration service, trains the initial machine learning model into a target machine learning model based on selection of a user, and automatically updates gradient information of the machine learning model in forward and reverse propagation processes of model training.

The embodiment of the invention provides a live broadcast system, a sound card device, an audio acquisition device, a monitoring device, a computer program product and a storage medium. In order to realize wireless connection between the sound card device and other devices in the live broadcast system, a first wireless transmission channel and a second wireless transmission channel can be arranged in the sound card device, and the two wireless transmission channels can work based on different wireless transmission protocols. The first wireless transmission channel can be used for transmission of voice data with a high real-time requirement between audio acquisition equipment and monitoring equipment, and the second wireless transmission channel can be used for transmission of accompaniment audio and other data with a low real-time requirement between accompaniment equipment. Through the mode, the audio acquisition equipment, the monitoring equipment, the accompaniment equipment and the like in the live broadcast system can be accessed to the sound card equipment in a wireless connection mode, and the construction process of the live broadcast system is simplified.

The invention provides a scene image construction method and device based on multiple sensors and electronic equipment. The method comprises the following steps: acquiring original image data of a power scene measured by a plurality of image sensors to obtain a plurality of groups of original image data, and preprocessing the plurality of groups of original image data to obtain a plurality of groups of preprocessed image data; pixel sparse processing is carried out on the preprocessed image data to obtain sparse image data, the pose of the image sensor is preliminarily determined according to the sparse image data, depth information of the image sensor is acquired, and the pose of the image sensor is adjusted according to the depth information; after the pose is adjusted, key frame image data are determined, an electric power scene image is constructed according to the key frame image data, and the key frame image data represent image data with the similarity degree of image contents of two adjacent frame images smaller than a preset threshold value. According to the invention, the problem of tedious steps of establishing the image of the complex power scene in the prior art is solved.

The invention relates to the technical field of classroom intelligent terminals, in particular to a classroom intelligent terminal integrating a micro host, network access and audio acquisition. According to the technical scheme, the classroom intelligent terminal integrating a micro host, network access and audio acquisition is provided. Comprising a main control unit, an acoustic array device, a network interface device, a deep learning audio processing unit, a multi-mode interaction device, an adaptive network technology component, an edge computing unit, a virtual reality and augmented reality device, a block chain module and a voice synthesis and emotion recognition module. The system provides more advanced, intelligent and interactive rich education experience, is expected to improve the learning effect and teaching efficiency, has potential revolutionary influence in the education field, and provides a more flexible, personalized and efficient learning environment.

The invention provides a time-varying parameter model identification method based on beta wavelet basis function expansion. As shown in the flow in figure 1, the method comprises the following steps: firstly, establishing a nonlinear autoregression time-varying parameter model by using a non-stationary time-varying signal, and determining the order of the model by using an FPE order determination criterion; performing linear weighted expansion on the model time-varying parameters by utilizing a first-order beta wavelet basis function, and converting a model time-varying parameter identification problem into a time-invariant parameter estimation and model effective item selection problem, namely obtaining a beta wavelet expansion time-invariant parameter model; selecting effective items of the model by adopting a classical orthogonal forward regression algorithm, determining the number of the effective items of the model in combination with an APRESS cross validation standard, eliminating redundant items in the expansion model, estimating corresponding time-invariant parameters of the model, and establishing a sparse model structure; and finally, in combination with the obtained effective items and corresponding parameters, obtaining a sparse nonlinear autoregression model and time-varying parameters thereof through reverse solution. Compared with an existing time-varying parameter identification method based on main B-spline multi-wavelet basis function expansion, the time complexity of the identification process can be effectively reduced, the identification precision of a sparse model is improved, and a new thought and a new calculation framework are provided for identification analysis of nonlinear time-varying parameter signals.

The invention relates to the technical field of robot control, and discloses a variable load balance control method, a balance control system and an experiment platform of a double-wheel-foot robot, and the method comprises the steps: building a simulation physical environment of the double-wheel-foot robot through a reinforcement learning experiment simulation platform; in a reinforcement learning experiment simulation platform, a reinforcement learning algorithm double-wheel-foot type robot variable load balance controller is used; a variable load balance controller is migrated and deployed to a real balance control system of the double-wheel-foot robot, and stable balance control in a real environment is realized in a double-wheel-foot robot experiment platform. By means of the method, the generation process of the control algorithm of the double-wheel-legged robot is simplified, the problem of real machine migration deployment is solved, and the reliability and maintainability of the system are improved. And meanwhile, the anti-interference capability and the stability of the double-wheel-foot type robot during variable load balance control are improved, and self-adaptive control of balance is achieved.

The invention relates to a FAP-targeted CAR-macrophage with an enhanced intercellular effect as well as a preparation method and application of the FAP-targeted CAR-macrophage. The CAR-macrophage contains a FAP specific CAR for targeting fibrosis and a burial effect enhancer Lgmn, the amino acid sequence of the FAP specific CAR for targeting fibrosis is as shown in SEQ ID NO. 1, and the nucleotide sequence of the FAP specific CAR for targeting fibrosis is as shown in SEQ ID NO. 2; the amino acid sequence of the cell burial effect enhancer is as shown in SEQ ID NO.3, and the nucleotide sequence of the cell burial effect enhancer is as shown in SEQ ID NO.4. The CAR-macrophage can specifically target an FAP target spot, can also enhance a cellular burial effect signal channel, realizes combination of CAR-macrophage therapy and intracellular degradation capability improvement, enhances intracellular rapid degradation and removal of phagocytized activated fibroblasts by expressing Lgmn protein, exerts and amplifies the phagocytic effect of the CAR-macrophage on the activated fibroblasts, and improves the activity of the CAR-macrophage on the activated fibroblasts. Therefore, an efficient anti-fibrosis effect is obtained.

The invention relates to the technical field of organoid construction, and discloses a heart organoid construction method which comprises the following steps: preparing a culture medium I containing CD lipid, ITS-X, L-AA2P, alpha-MTG, insulin, FGF2 and a GSK-3beta inhibitor; preparing a culture medium II containing CD lipid, ITS-X, L-AA2P, alpha-MTG, insulin, FGF2 (fibroblast growth factor 2) and VEGFA (vascular endothelial growth factor A); the method comprises the following steps: digesting a human induced pluripotent stem cell mass, suspending the human induced pluripotent stem cell mass in a culture medium I, inoculating the human induced pluripotent stem cell mass into an ultra-low adsorption cell culture plate with a U-shaped hole bottom, culturing for 36-40 hours, removing the culture medium I, adding a culture medium II, and culturing until a heart organ is formed. In the method provided by the invention, two culture media are sequentially used for performing two-stage differentiation culture, namely, the heart organoid can be constructed from the human induced pluripotent stem cells dispersed after digestion, so that the construction process of the heart organoid is simplified, the construction time is shortened, and the operation difficulty is reduced.

The invention discloses a time convolutional neural network model fusing an attention mechanism, a power system dynamic state estimation method, system and device and a medium, and the model comprises an input layer, an output layer, a full connection layer and a plurality of TCN modules, the input layer, each TCN module, the full connection layer and the output layer are connected in sequence, and the TCN modules are connected in sequence. And a self-attention layer and an activation function module are sequentially arranged between the adjacent TCN modules and between the last TCN module and the full connection layer. The model, the method, the system, the equipment and the medium can improve the accuracy of dynamic state estimation of the power system.

The invention provides a modular windproof shed for steel structure aerial work and a construction method, and relates to the field of windproof sheds, the modular windproof shed comprises a welding platform, and three modular supports are fixedly installed on the four side faces of the top of the welding platform in an array mode. According to the welding platform, the modular support is arranged, the prefabricated part is divided into the upper part and the lower part, the windproof cloth is wound around the inner cavity of the upper portion of the prefabricated part and installed on the four side faces of the welding platform through the modular support, then the windproof cloth is pulled out through the fixing assembly, and the top and the upper portion of the welding platform are shielded; and meanwhile, the inner side protecting net is slidably mounted on the inner side of the upper portion of the prefabricated part, the inner side protecting net coincides with the bottom protecting net after being pulled down, the leaking holes are staggered and shield the leaking holes, the bottom protecting net can be sealed, the windproof effect is achieved, gravel is prevented from falling, and a good protection effect is achieved on constructors.

The invention discloses a petrochemical product life cycle carbon footprint accounting method and tool, and solves the problems of inaccurate result caused by model black box operation, poor applicability to specific products and neglect of carbon emission of key links under a complex process in existing petrochemical product carbon footprint evaluation. The method comprises: determining a target product and a system boundary; establishing a technological process model according to the target product production process; the technological process model is analyzed and divided into a plurality of modules; performing list analysis on the modules to obtain material data related to carbon footprints; establishing a product carbon footprint accounting model of the module based on a life cycle evaluation method; and according to the carbon footprint accounting model of each product, calculating the carbon footprint of the petrochemical product and carrying out result analysis. Systematic carbon footprint evaluation is carried out according to the life cycle, modular processing is carried out on the technological process, and under the conditions of complexity of a production system and data incompleteness, accuracy and high efficiency of carbon footprint evaluation are ensured.

The embodiment of the invention discloses an animation generation method and device, a storage medium and electronic equipment. The method comprises the following steps: reading animation configuration information of a target event animation by adopting a first object; configuring a second object for each virtual character through the first object based on the animation configuration information; executing the event node of the virtual character configured for the second object through the second object; when the event node executed by the second object is the performance synchronization node, not entering a next event node after the performance synchronization node, and sending a completion instruction for the performance synchronization node to the first object; and if the first object receives a completion instruction which is sent by all target second objects to which the same performance synchronization node belongs and aims at the same performance synchronization node, controlling the target second objects to execute a next event node of the same performance synchronization node so as to generate a target event animation. Therefore, the event animation generation process can be effectively simplified, the animation production cost is reduced, and the animation generation efficiency is improved.

The embodiment of the invention provides a finite element-based near-shore ocean model BMI configuration method, which comprises the following steps: aiming at a finite element-based near-shore ocean model, namely a Thetis model, constructing a configuration file of a basic model interface BMI, and the configuration file is used for inputting an initialization function of the BMI; constructing an analyzer capable of reading and analyzing the content of the configuration file, and mapping the content of the configuration file into the Thetis model; and when initialization construction is performed on the Thetis model, editing is performed through a BMI according to the content of the configuration file mapped to the Thetis model, an initialization function is constructed, and a Thetis model initialization file is formed through the initialization function. By setting the configuration file, the construction process in the initialization stage is simplified, the function of constructing the model according to the information of the configuration file is realized, and the tedious operation in the initialization stage in the prior art is improved.

The present invention discloses a method for generating an application update package, a smart terminal and a storage medium, the method comprising: obtaining a target function of an application to be updated; if the target function meets the preset condition, adding the update data corresponding to the target function to the installation package file of the application to be updated, and obtaining the update package of the application to be updated. The present invention can generate a new update package by obtaining the target function of the application to be updated, and adding the update data corresponding to the target function to the installation package file of the program to be updated according to whether the target function meets the preset condition. There is no need to update all the data of the program to be updated. Only the required update data needs to be added to realize the generation of the update package, which simplifies the generation process of the update package and shortens the overall upgrade cycle of the application.

The invention discloses a double-shaft type optical speed detector and a calibration method, and particularly relates to the technical field of detectors. The double-shaft type optical speed detector comprises a double-optical-path detection module, a sample adaptation module, a speckle manufacturing and detecting module, a data processing and calibration module and a display and control module. According to the double-shaft type optical speed detector and the calibration method, the light path building process is simplified through the arrangement of the integrated light path module, a user can carry out detection only through simple operation, the operation convenience is improved, the detection capacity for sample characteristic changes is effectively enhanced through the arrangement of the double-light-path detection module, and the detection accuracy is improved. The high-sensitivity detection is realized, the sample adaptation module is arranged to adapt to various samples, the universality of the device is improved, and meanwhile, the speckle manufacturing and detection module is arranged to realize high-quality and high-adaptability speckle manufacturing and detection. And the data processing and calibration module and the display and control module ensure the accuracy of data and the intuition of result display.