8results about How to "Increase dominance" patented technology

The application discloses a steel slag and recycled asphalt mixture thin layer based on directional migration of aged asphalt and a preparation method thereof, and belongs to the technical field of road engineering materials. The application also discloses a steel slag adaptive migration induction composite recycling agent. The steel slag adaptive migration induction composite recycling agent is used for permeating and activating the surface aged asphalt of RAP, cooperating with the porous adsorption and interface induction of pretreated steel slag, realizing directional migration and reconstruction distribution of the aged asphalt from the surface of RAP aggregate to the interface of steel slag, significantly reducing the harm of aged asphalt inferior phase, strengthening the dominant role of new asphalt, and synchronously reducing the risk brought by the volume stability of steel slag. The application prepares the recycled asphalt mixture thin layer through RAP preheating, primary permeation and activation regeneration, secondary migration induction regeneration and mixture molding, the thin layer is excellent in low-temperature crack resistance, water stability and durability, can greatly improve the utilization rate of RAP and steel slag solid waste, and is suitable for asphalt pavement preventive maintenance, thin layer overlay and micro-surfacing engineering.

The utility model discloses an adjustable switch for a computer network, which comprises a machine body, a cover plate is mounted outside the machine body, and a mounting frame is fixedly connected to the back of the machine body. According to the utility model, by rotating the bidirectional threaded rod, the two threaded sleeves can move towards or away from each other along the outside of the bidirectional threaded rod, and the two mounting sleeves can move towards or away from each other synchronously, so that the two mounting sleeves can be matched with the two formed mounting holes in a spacing manner, the convenience in the mounting process can be realized, accurate measurement and punching are not needed, and the mounting efficiency is improved. Heat dissipation of the interior of the machine body can be achieved through the combination of the air inlet holes and the heat dissipation holes, when heat dissipation is poor in summer or a narrow space and the temperature in the machine body rises, the temperature sensor can conduct real-time monitoring, and when the temperature reaches a preset value, the exhaust fan starts to work synchronously; outside air can be accelerated to enter the machine body from the air inlet holes, and meanwhile high-temperature air in the machine body can be rapidly exhausted from the heat dissipation holes.

The application provides a grid synchronization control method, device, equipment and medium of a photovoltaic inverter, comprising: collecting three-phase voltage signals at a grid point of common connection in real time, and preprocessing the three-phase voltage signals to obtain q-axis voltage residuals; serializing sampling the q-axis voltage residuals to construct a short-time phase deviation time sequence; inputting the short-time phase deviation time sequence into a pre-trained recurrent neural network model to obtain a predicted phase angle increment; based on the predicted phase angle increment, combining a photovoltaic grid-connected working condition, and calculating a synchronization phase angle; and based on the synchronization phase angle, controlling the grid synchronization phase of the photovoltaic inverter. The phase deviation is predicted through the recurrent neural network, the phase error problem caused by the lag of the traditional PI control is overcome, and the accuracy and stability of the grid synchronization of the photovoltaic inverter are effectively improved.

The application discloses a kind of multimodal sentiment analysis method, device, equipment and storage medium.The method includes: constructing the sentiment analysis dataset containing text, audio and visual sequence and inputting pre-training model, extracting each modality initial feature using feature coding module, comparing learning and dynamic fusion are carried out through modal common information processing module to obtain cross-modal common feature, with the aid of modal specificity information processing module, feature enhancement and pooling are implemented to generate global enhanced features, finally, each kind of feature is spliced and regression prediction is executed to output sentiment intensity prediction value by fusion prediction module;Since the application cooperates modeling modal common and specificity information, the modal heterogeneity is considered and the average processing bottleneck is broken, different dimension features can be dynamically distinguished, the modal conflict can be effectively relieved, and the prediction accuracy and robustness of sentiment analysis can be significantly improved.

This disclosure provides a method, apparatus, device, and medium for generating adversarial perturbations for voiceprint recognition. The adversarial perturbation generation method includes: acquiring a training voiceprint sample set; initializing an adversarial sample generation network; determining a target recognition object for each original voiceprint sample in the training voiceprint sample set; inputting the original voiceprint samples into the adversarial sample generation network to obtain adversarial voiceprint samples; inputting the adversarial voiceprint samples into a voiceprint recognition network to obtain a first recognition result vector; determining a sample loss function for the adversarial sample generation network based on the original voiceprint samples, the adversarial voiceprint samples, a first probability, and a second probability; training the adversarial sample generation network based on the sample loss function to generate adversarial perturbations. Embodiments of this disclosure can improve the efficiency of generating adversarial perturbations and also enhance the dominance and stealth of the adversarial perturbations. Embodiments of this disclosure can be applied to artificial intelligence, communication security, etc.

The application discloses a kind of multimodal sentiment analysis method, device, equipment and storage medium.The method includes: constructing the sentiment analysis dataset containing text, audio and visual sequence and inputting pre-training model, extracting each modality initial feature using feature coding module, comparing learning and dynamic fusion are carried out through modal common information processing module to obtain cross-modal common feature, with the aid of modal specificity information processing module, feature enhancement and pooling are implemented to generate global enhanced features, finally, each kind of feature is spliced and regression prediction is executed to output sentiment intensity prediction value by fusion prediction module;Since the application cooperates modeling modal common and specificity information, the modal heterogeneity is considered and the average processing bottleneck is broken, different dimension features can be dynamically distinguished, the modal conflict can be effectively relieved, and the prediction accuracy and robustness of sentiment analysis can be significantly improved.

This application discloses a method and system for identifying privately installed energy storage loads based on electricity consumption behavior patterns, belonging to the field of privately installed energy storage identification technology. The method includes: obtaining hierarchical load sets by performing hierarchical analysis of historical load data based on differences in identification results; reconstructing typical load curves by morphological clustering of daily load curves for each hierarchical load set; constructing baseline load curves using rigid load confidence weight coefficients and typical load curves of each hierarchical load set; obtaining energy storage behavior curves under different user behavior patterns based on the baseline load curves and typical load curves; obtaining privately installed energy storage load characteristics corresponding to the user behavior patterns based on the energy storage behavior curves; and performing privately installed energy storage load identification based on the privately installed energy storage load characteristics. The beneficial effects of this application are: improving the accuracy and comprehensiveness of privately installed energy storage load identification by performing identification of privately installed energy storage loads with different energy storage behaviors.

The invention relates to an intelligent alignment compensation method for assembly of a liquid crystal panel and a backlight module, and aims to solve the problems of dynamic pose deviation and weight mismatch caused by material batch difference, nonlinear deformation and environmental factors in a high-precision fitting process. According to the core technology, an industrial camera array and a multi-source sensor are used for collecting multi-dimensional micro texture and environment data, a fingerprint spectrum of intrinsic deformation characteristics of a material is established in a fusion mode, spectrum matching and weight self-adaptive calibration are carried out in combination with real-time working conditions and visual feedback, and six-degree-of-freedom micro dynamic correction is achieved through FPGA acceleration driving control. According to the scheme, the sub-pixel-level precision in the attaching process of the liquid crystal panel and the backlight module is effectively improved, the nonlinear deformation trend of materials is restrained, the control instruction response speed is optimized, continuous and accurate calibration of self-adaptive compensation weights among batches is guaranteed, and the process consistency and the automation level are improved.