19results about How to "Improve persuasiveness" patented technology

The invention relates to the technical field of intelligent voice interaction, in particular to an AI mobile phone voice interaction method oriented to automatic marketing, which comprises the following steps of: providing a comprehensive basis for personalized marketing and improving the marketing pertinence by recognizing a user emotional state and a real-time user intention in parallel and mastering the user state; an emotion state transition network is dynamically constructed and updated, key indexes are extracted, and a user emotion change rule is analyzed, so that an interaction strategy is accurately adjusted; semantic fragments are recombined by combining emotional stability and emotional infection degree indexes, adaptive dynamic marketing verbal skill is generated, the attraction and persuasion of the verbal skill are enhanced, and the marketing effect is improved; the local NPU is utilized to synthesize emotional voices and superpose features, so that natural and vivid interaction experience is provided, and recognition of a user on marketing content is enhanced; through dynamic decision-making verbal skill strategy cross-scene switching, timely adjustment is carried out according to user changes, marketing strategy stiffness is avoided, and the marketing success rate is guaranteed.

The invention discloses a tight-lock coupler intelligent tensile testing machine and a testing method thereof, and belongs to the technical field of tight-lock coupler test.The tight-lock coupler intelligent tensile testing machine comprises a mounting bottom plate and an electric control cabinet, and a support for supporting a tight-lock coupler to be detected is mounted on the surface of the mounting bottom plate; a tensile connecting frame for connecting the tight-lock coupler is mounted on the surface of the bottom plate on one side of the support, an integrated design of'tensile force detection and visual detection 'is innovatively adopted, mechanical parameter acquisition and visual deformation observation are combined, traditional mechanical data such as tensile force and displacement are obtained, and visual characteristics such as fine deformation and crack initiation are captured; precise synchronization of pulling force application, displacement collection and camera shooting is achieved through the synchronous controller, the real-time corresponding relation of pulling force-displacement-visual deformation is established, the problems that an existing device is single in detection dimension and poor in data relevance are solved, and the potential quality hazard checking capacity and the persuasion of a detection result are improved.

The application discloses a kind of ship intelligent navigation algorithm simulation verification system and test method, the system uses four-layer modular structure, including: virtual navigation environment module, standardization data interaction module, algorithm execution module, quantitative evaluation module;Between each module, standardization data interaction module is realized two-way data transmission, forms the complete simulation verification system capable of independent test and closed-loop operation.The method, using the system, the steps are: step 1: build inland virtual navigation scene, step 2: select test mode and configure algorithm, step 3: start simulation and data acquisition, step 4: evaluation index calculation, step 5: generate verification report.The algorithm unit of the application can be independently accessed to test, without overall reconstruction, perception, decision-making, control algorithm can be quickly adapted, greatly reduce the difficulty of integration debugging, improve algorithm development and verification efficiency, effectively shorten the intelligent ship development cycle.

The application discloses a traditional Chinese medicine property analysis system and method, and a computer readable storage medium. The system comprises an information acquisition unit, a first analysis unit, a quantification unit and a second analysis unit. The method comprises grouping patients with consistent conditions and grouping traditional Chinese medicines according to different influencing factors; analyzing the influence of different influencing factors of traditional Chinese medicines on treatment effects; analyzing the quantitative relationship between the dosages of traditional Chinese medicines with different influencing factors and the dosages of traditional Chinese medicines required to achieve the same treatment effects; and analyzing the influence of influencing factors of traditional Chinese medicines on the properties of traditional Chinese medicines. The application analyzes the influence of different influencing factors of traditional Chinese medicines on treatment effects, further obtains the influence of influencing factors of traditional Chinese medicines on the properties of traditional Chinese medicines, and thus obtains the dosages of traditional Chinese medicines suitable for the current situation according to the quantitative relationship between the dosages of traditional Chinese medicines with different influencing factors and the dosages of traditional Chinese medicines required to achieve the same treatment effects, which is favorable to increasing the accuracy of the dosages of traditional Chinese medicines, strengthening the comprehensive understanding of the properties of traditional Chinese medicines, enhancing the modernization degree of traditional Chinese medicine, improving the persuasiveness and reliability of traditional Chinese medicine, and being favorable to the international development of traditional Chinese medicine.

This invention relates to the field of simulation demonstration devices, providing a water-voltaic effect simulation device based on electrolytic color development, comprising a water-voltaic power generation module and an electrolytic color development module. The water-voltaic power generation module includes a water-voltaic effect thin film and a circulation mechanism, while the electrolytic color development module includes a transparent electrolytic cell, an inert electrode pair, and a standard electrolyte. The weak electrical signal generated by the water-voltaic power generation module is directly applied to the inert electrode pair, directly driving the electrolytic reaction within the transparent electrolytic cell without the need for external amplification circuitry. The electrolytic color development module simultaneously displays the instantaneous power and accumulated charge of the water-voltaic power generation module through the cathode bubble generation rate and the color change area of ​​the acid-base indicator near the cathode. This invention requires no external power supply amplification, intuitively demonstrates the conversion relationship between electrical energy and chemical energy, supports multi-water quality variable control experiments, and is suitable for teaching demonstrations in university physics, materials, and environmental courses.

The invention discloses a curriculum commodity personalized recommendation method and device, a terminal and a storage medium, and relates to the field of commodity recommendation. The method comprises the following steps: acquiring client target data and multi-dimensional current situation data to perform state quantification to obtain a quantized state set, constructing a course logic relation graph, mapping knowledge level differences to graph effective nodes, performing topological sorting and time resource filtering to obtain candidate learning paths, and performing learning on the candidate learning paths. And calculating the comprehensive gain value of the candidate learning path, and selecting the path corresponding to the highest value as a personalized recommendation path. Meanwhile, the method also comprises a rapid recommendation step for new customers or data sparse customers. The technical effects of providing a personalized course commodity recommendation scheme according to the actual condition of the customer, improving the accuracy and effectiveness of recommendation, saving the learning time for the customer, improving the learning effect and facilitating the new customer to quickly obtain proper recommendation are achieved.

The invention relates to the technical field of optical surface shape detection, in particular to an optical surface shape full-band error analysis method based on a frequency domain attention mechanism, and the method comprises the steps: obtaining a surface shape detection result data set and a full-band error data set; based on spatial distribution of different frequency band information in a frequency domain, constructing a frequency domain attention mechanism, and obtaining and constructing a low-frequency error extraction neural network, an intermediate-frequency error extraction neural network and a high-frequency error extraction neural network with the frequency domain attention mechanism; respectively training the three error extraction neural networks by using the surface shape detection result data set and the full-band error data set to obtain three corresponding error extraction neural models; and respectively inputting the surface shape detection result of the optical element to be detected into the three error extraction neural models, and respectively extracting a low-frequency error, an intermediate-frequency error and a high-frequency error. The method provided by the invention has relatively high universality, does not introduce human subjective errors, and is high in analysis precision.

The invention provides a biomarker for predicting the treatment response of an ovarian cancer patient to a VEGFR (vascular endothelial growth factor receptor) inhibitor and application of the biomarker, and finds that the fat volume of the ovarian cancer patient can be used as the biomarker for predicting the curative effect of the VEGFR inhibitor to tumors. Based on two markers of visceral fat volume and subcutaneous fat volume, an SAS trajectory analysis model is constructed, and clinical benefit people of an ovarian cancer VEGFR inhibitor treatment scheme are screened out; further in-vitro co-culture and in-vivo animal experiments prove that the existence of fat cells can specifically enhance the anti-tumor effect of the VEGFR inhibitor, and clinical correlation is explained from a biological mechanism; the invention provides a new tool and theoretical basis for realizing individualized precise medication of ovarian cancer targeted therapy.

The application provides a kind of thermal protection interlock logic knowledge base construction method and system, comprising: based on graph database construction knowledge graph;Combining the initial knowledge item generated by preset hazard dimension, and retrieve the citation basis related to initial knowledge item from multi-source thermal data, the citation basis is associated with initial knowledge item, form the knowledge item after association;The associated knowledge item is verified in multiple rounds, and the verification includes calling the existing knowledge in the knowledge graph for logical self-checking, cross verification with historical knowledge items and backstepping verification based on accident cases, and output the knowledge item that passes the verification;Continuously monitor the thermal data source, generate knowledge update proposal based on the knowledge item that passes the verification, and update the knowledge graph and knowledge item after compatibility verification and artificial review of the update proposal.The application reduces the risk of knowledge deviation caused by human error through automated process and multiple verification mechanisms.

The invention belongs to the technical field of obstetrics and gynecology disease prediction, and particularly relates to a premature fetal membrane premature rupture prediction marker based on maternal circulation exosome microRNA and an application kit. According to the invention, placentas, fetal membranes and plasma exosomes of pregnant women with full-term birth and premature birth premature rupture of fetal membranes are collected for sequencing, the fetal membrane-derived exosome hsa-miR-145-3p which can be detected in the plasma exosomes is screened out in combination with a verification set, and the cell source and the premature birth promoting effect of the fetal membrane-derived exosome hsa-miR-145-3p are respectively clarified at a cell level and an animal level; and finally, by detecting the level of the plasma exosome hsa-miR-145-3p of the pregnant 12 (+ 1)-17 (+ 6) perimaternal body, the efficiency (AUC = 0.833) of the exosome in predicting the occurrence of premature rupture of fetal membranes in premature delivery is illustrated. According to the method, the high-risk crowd of the pPROM can be predicted through a noninvasive method in the early and middle stages of pregnancy, and the method has guiding significance for subsequent prevention and intervention of the high-risk crowd.

The application discloses an interpretable analysis and decision sharing verification method and system for a colorectal cancer prognosis model, and relates to the field of medical artificial intelligence interpretability. The method comprises the following steps: performing gradient weighted class activation mapping analysis on the prognosis model to generate an image heat map; calculating the contribution degree of multi-modal features by using a SHAP interpreter; constructing an integrated visualization interface to present the patient data, model prediction and the above-mentioned explanation results to doctors; the doctors perform independent risk assessment based on the interface information; and finally, the decisions of the doctors and the model are compared to evaluate the auxiliary performance of the model. Through multi-level explanation and innovative doctor-model decision sharing verification mechanism, the transparency and clinical credibility of the complex AI prognosis model are significantly improved, the value of time series data in dynamic risk assessment can be verified, and the clinical landing application of the AI model is effectively promoted.

The application claims a cascaded feature extraction method for agricultural product price prediction, belonging to the technical field of artificial intelligence and agricultural economic analysis. The method adopts a three-level cascaded processing architecture: first, a filter-type coarse screening is realized through K-neighbor mutual information estimation, realizing preliminary dimension reduction; second, embedded feature selection is realized through an XGBoost model, and core prediction features are screened out; finally, multi-scale enhancement is realized through discrete wavelet decomposition on the time series core features, and trend and fluctuation components with clear physical meaning are constructed. Based on the processed enhanced features, a bidirectional long short-term memory network prediction model is constructed, and an ablation experiment of the system is designed to verify the effectiveness of each level of processing. Through systematic feature extraction and enhancement, the precision and stability of agricultural product price prediction are significantly improved, providing reliable technical support for market early warning and agricultural economic decision-making.

The invention discloses a Chinese yam decoction piece origin traceability method based on GC-MS and hyperspectral imaging fusion and application. The method comprises the following steps: S1, preparing a sample; s2, data acquisition; the method specifically comprises the following steps: S21, acquiring hyperspectral data; s22, GC-MS data acquisition; S3, multi-source data feature analysis; s4, feature screening and data fusion; s5, model construction and performance verification; and S6, constructing a fusion fingerprint spectrum. The data fusion model overcomes the problems of easy overfitting and poor generalization ability of a single technology, and the traceability result is more reliable. The classification accuracy of the random forest model based on fusion data reaches 92.3%, which is significantly higher than that of a single data source method. A unique visual identifier is provided for each producing area by fusing the fingerprints, and technical transformation and industrial popularization are facilitated.

This invention relates to a chip for identifying polysaccharides from traditional Chinese medicine containing the structure →4)-β-D-Manp-(1→ and its application, belonging to the field of biochip technology. The chip of this invention comprises a solid-phase support and a microarray system, wherein the microarray system is fixed on the surface of the solid-phase support. Using a glass substrate treated with hydrazide as the carrier, the invention precisely spots the target polysaccharide, polysaccharide standards, and negative / positive controls using a spotting instrument to construct a polysaccharide chip containing 16 subarrays. After blocking the non-specific binding sites of the chip with a blocking buffer, fluorescently labeled LM21 antibody is added to the subarrays for incubation. By collecting fluorescence signals, the relative fluorescence unit value is obtained, directly reflecting the binding strength between the polysaccharide and the LM21 antibody. This invention is simple to operate, has high detection sensitivity, and strong structural recognition specificity, and can be widely used for the rapid screening and precise structural characterization of active polysaccharides from traditional Chinese medicine, providing an efficient technical means for the development and utilization of polysaccharides from traditional Chinese medicine.

The application discloses a kind of construction methods of double-variable structure optimization scheme for inhibiting flow corrosion of stop valve, the method comprises the following steps: according to the demand of inhibiting flow corrosion of stop valve, two structure variables of optimization scheme are determined;Initial control group, single variable group and double variable group are set up and numbered;The valve model corresponding to the numbered scheme is modeled and its three-dimensional flow passage model is extracted;The flow passage model is meshed;For multiple model schemes, simulation analysis is carried out based on CFD for each scheme, and calculation data is obtained;Data and image processing is carried out on the calculation data, and flow corrosion cloud chart and maximum corrosion rate statistical chart are obtained;The flow corrosion cloud chart and the maximum corrosion rate statistical chart are compared;Determine the optimal structure optimization scheme based on the comparison result.The construction method is double-variable structure optimization for stop valve, greatly improves the effect of inhibiting flow corrosion of stop valve, and has sufficient control at the same time, enhances the persuasiveness of optimization scheme.

This application discloses a method, apparatus, medium, and device for intervening in misinformation on social networks based on graph causal reasoning. It constructs a user influence graph to select trust-oriented users as nodes, estimates individual treatment effects using a causal forest algorithm to determine high-value intervention targets, generates personalized intervention text using efficient parameter fine-tuning technology, and injects it into the social network for real-time monitoring and updates, achieving precise and efficient misinformation intervention. This method constructs a user influence graph containing time-attitude trajectories and semantic context sets, employs a causal forest algorithm under a dual machine learning framework to select key users, constructs a multi-dimensional policy space through the SMCR propagation model, and generates personalized intervention responses by combining counterfactual exploration mechanisms and efficient parameter fine-tuning technology. It can increase the individual belief reversal rate by 7.9%, reduce the final infection rate of misinformation by 35.2%, and achieve the suppression effect of traditional methods requiring only 5% of intervention resources, while requiring 15% of the resources.

This invention discloses a method for stability analysis of base stations in a reservoir dam safety monitoring and control network. Addressing the shortcomings of existing technologies, such as lack of physical modeling, low signal separation accuracy, and incomplete interference removal, this method obtains millimeter-level coordinate time series through GNSS raw data preprocessing; it finely eliminates non-tidal atmospheric / oceanic loads and non-hydrological interferences such as the thermal expansion effect of observation piers and bedrock; it constructs a hydrological load model based on reservoir contour, water level, and rock mass parameters, and verifies it through both finite element simulation and a half-space elastic model; it employs a VBPCA-FastICA combined algorithm to accurately extract hydrological load signals; and it completes a quantitative stability evaluation by combining short-time repeatability, station velocity, and residual RMS multi-dimensional indicators. This invention achieves bidirectional verification of hydrological load physical forward modeling and observation data, accurately distinguishes between tectonic and hydrological non-tectonic displacements, significantly improves signal separation and stability assessment accuracy, and is suitable for reservoir dam hydrological-dominant monitoring scenarios. It can be used for stability determination and control network optimization of base stations in large-scale water conservancy projects.

The invention discloses a bionic hoof simulation device based on biomechanical simulation and an experience system, the device comprises a wearing part and a mechanical transmission mechanism, the wearing part extends along the longitudinal direction and defines a coating space, the mechanical transmission mechanism is fixedly arranged on the wearing part, and the mechanism enables a load transmission part to be arranged at the near end of a tail end joint of an experiencer through a rigid supporting piece; a main supporting assembly with a first friction characteristic is fixedly arranged at the far end of the device, and an auxiliary braking assembly with a second friction characteristic is fixedly arranged on the outer side of the wearing part. A space compensation gap is formed between the ground contact working surfaces of the main supporting assembly and the auxiliary braking assembly, so that the device is switched between a sliding state in which only the main supporting assembly abuts against the plane and a braking state in which the auxiliary braking assembly intervenes along with the change of the inclination angle of the wearing part. According to the invention, the load is conducted by bypassing the joint through the rigid support, the kinematic mechanics logic of the undules is simulated through cooperation of multiple assemblies, and the motion safety is ensured while the simulation cognitive experience is improved.

The application belongs to the technical field of book recommendation, and particularly relates to a book recommendation method and system based on a knowledge graph. The method comprises the following steps: S1, acquiring book related data and book system user related data; S2, cleaning the book related data and the book system user related data; S3, constructing a knowledge ontology according to the cleaned book data, and generating a classified book knowledge graph; S4, constructing a knowledge ontology according to the book system user related data and user system use condition information, and generating a user knowledge ontology and a user portrait knowledge graph; and S5, generating a personalized book recommendation for a user according to the book knowledge graph, the user knowledge ontology and the user portrait knowledge graph, and combining a hybrid sequence recommendation algorithm. The application has the characteristics of combining a deep learning technology, using a knowledge graph to represent book knowledge information and user interest conditions, and being highly automated, dynamic and efficient.