Abstract: The present invention discloses a multi-energy complementary system for a co-associated abandoned mine and a use method. The multi-energy complementary system for a co-associated abandoned mine includes a mining mechanism, a grouting mechanism and an energy mechanism. In the present invention, the mining of coal and uranium resources is realized through the mining mechanism, the subsidence and seepage reduction of the stratum is realized through the grouting mechanism, and the effective utilization of waste resources is realized through the energy mechanism. Finally, with the efficient cooperation of the three mechanisms, safe and efficient development and utilization of co-associated resources in the full life cycle are realized, and the purposes of green and efficient mining of coal and uranium resources and secondary development of a coal seam goaf are achieved, thereby facilitating the realization of dual-carbon goals and the development of low-carbon green energy.

Abstract: A fault detection method includes: obtaining a video quality parameter of a monitored video stream, where the video quality parameter is determined according to a packet loss recovery method of the monitored video stream, the video quality parameter includes an effective packet loss factor, and the effective packet loss factor is used to indicate effectiveness of network packet loss recovery performed by using the packet loss recovery method of the monitored video stream; and performing fault detection based on the video quality parameter of the monitored video stream.

Abstract: An intelligent experimental device for collaborative mining of associated resources includes a signal transmission mechanism, a pressure maintaining mechanism, a feeding mechanism, and a reaction mechanism. The signal transmission mechanism includes a centralized controller, an annunciator, signal receivers, a power supply, a power cord, signal transmitters, and signal sensing valves. The pressure maintaining mechanism includes ambient and axial pressure oil chambers, ambient and axial pressure pumps, ambient and axial pressure liquid distribution tanks, a comprehensive pressure distribution pipe, and hydraulic transmission pipes. The feeding mechanism includes monitoring analyzers, temperature controllers, solution transfer pipes, seepage pumps, mixture conveying pipes, a comprehensive liquid distributor, an aggregate chamber, a liquid chamber, an oil chamber, a gas chamber, a mixing chamber and an analytical purifier.

Abstract: The present disclosure provides a method for gait recognition based on visible light, infrared radiation and structured light. According to the method, three types of raw image data are obtained from a visible light sensor, an infrared sensor, and a structured light sensor, then image processing and multi-sensor image fusion are improved to obtain a fused image, and gait recognition is performed based on the fused image. The method effectively improves the robustness of a recognition algorithm, and can realize accurate identification of individuals under various extreme conditions. The method has good adaptability and has a broad application prospect.

Abstract: The present disclosure discloses a method for improving the performance of concrete aggregates, comprising the following steps: (1) adding composite microbial powders, recycled aggregates and water into a stirring pot in a certain ratio to be continuously and uniformly stirred; (2) placing the recycled aggregate obtained in step (1) and another microbial powder in a vacuum device so as to fill the microbial powder into the cracks of the recycled aggregate in a negative-pressure environment; and (3) spraying a calcium source solution to the surface of the recycled aggregate obtained in step (2) at an interval of 5-6 hours for repeating 3-5 times to maintain the wet surface of the recycled aggregate.

Abstract: A federated learning method includes: each second device in a plurality of second devices first obtains data distribution information and sends the data distribution information to a first device. The first device receives the data distribution information from the plurality of second devices participating in federated learning. The first device selects a matched federated learning policy based on the data distribution information. The first device sends a parameter reporting policy corresponding to the federated learning to at least one second device in the plurality of second devices. A second device that receives the parameter reporting policy is configured to obtain second gain information based on the parameter reporting policy and a current training sample, and the second gain information is for obtaining a second model of the second device.

Abstract: A processor-implemented method is disclosed.

Abstract: The present disclosure discloses a method for improving the performance of concrete aggregates, comprising the following steps: (1) adding composite microbial powders, recycled aggregates and water into a stirring pot in a certain ratio to be continuously and uniformly stirred; (2) placing the recycled aggregate obtained in step (1) and another microbial powder in a vacuum device so as to fill the microbial powder into the cracks of the recycled aggregate in a negative-pressure environment; and (3) spraying a calcium source solution to the surface of the recycled aggregate obtained in step (2) at an interval of 5-6 hours for repeating 3-5 times to maintain the wet surface of the recycled aggregate.

Abstract: A method for providing a dynamic user interface for navigating user account data is disclosed. The method includes: performing a first data transfer from a user account; updating an interaction model for the user account based on the first data transfer; receiving, from a client device associated with the user account, a query having at least one query term; determining, based on the interaction model and the at least one query term, that the query maps to a user intent associated with the first data transfer; and in response to determining that the query maps to a user intent associated with the first data transfer, providing, to the client device, a search result based on the first data transfer.

Abstract: A sample data annotation system includes an edge node and a central node. The edge node obtains a key feature of sample data, determines, based on the key feature, whether the sample data is unknown sample data, when the sample data is unknown sample data, performs annotation processing on the sample data to obtain a first annotation result, and sends the first annotation result to the central node. The central node receives the first annotation result, and determines whether the first annotation result indicates successful annotation; and when the first annotation result indicates that the unknown sample data is successfully annotated, performs consistency processing on the first annotation result to obtain a second annotation result, or when the annotation result indicates that the unknown sample data fails to be annotated, performs annotation processing on the unknown sample data to obtain a third annotation result.

Abstract: A method, an apparatus, and a computing device for constructing a prediction model, and a storage medium are disclosed, and relate to the field of artificial intelligence technologies. The method includes: obtaining, based on a target dataset of a target prediction scenario and/or scenario information of the target prediction scenario, model search space corresponding to the target prediction scenario; performing model training based on the target dataset and models and hyperparameters that are included in the model search space, to obtain trained prediction models; and obtaining, based on evaluation results of the trained prediction models, a prediction model corresponding to the target prediction scenario. Efficiency of constructing the prediction model can be improved.

Abstract: A modeling method and an apparatus are disclosed. The method includes: obtaining a first data set of a first indicator, and determining, based on the first data set, a second indicator similar to the first indicator; and determining a first model based on one or more second models associated with the second indicator. The first model is used to detect a status of the first indicator, and the status of the first indicator includes an abnormal state or a normal state. The second models are used to detect a status of the second indicator, and the status of the second indicator includes an abnormal state or a normal state.

Abstract: In certain embodiments, a forwarding device receives at least one service flow. The forwarding device obtains service information of the at least one service flow, where the service information of the service flow includes identification information of a network object to which the service flow belongs and M key performance indicators KPIs of the service flow. M is an integer greater than o, and the network object includes one or more devices. The forwarding device sends detection information to a first device, where the detection information includes the service information of the at least one service flow or a feature set obtained based on the service information of the at least one service flow. The detection information is used to detect whether the network object is in a faulty state.

Abstract: A soil solidification material based on solid waste and bioenzyme, and a preparation method thereof are disclosed. The soil solidification material is composed of the following components in parts by weight: recycled aggregate 22-35 parts, steel slag 20-30 parts, high-calcium fly ash 16-24 parts, the bioenzyme 5-15 parts, an inorganic adsorbent 10-18 parts, an organic adsorbent 8-20 parts, industrial waste gypsum 25-35 parts, an activator 20-30 parts, sodium citrate 1-3 parts, and slaked lime 0.02-0.2 parts. The present disclosure adopts the recycled aggregate, the steel slag, the industrial waste gypsum and the high-calcium fly ash as the main components of the soil solidification material to reduce the cost. The soil solidification material of the present disclosure prepared by optimizing the proportion is capable of significantly improving the engineering properties of the soil or the mixed contaminated soil, and has significant economic and environmental benefits.

Abstract: A model update system, which may be applied to the network control field, includes a site analysis device and a first analysis device. The site analysis device is configured to: receive a first model sent by the first analysis device; train the first model by using a first training sample to obtain a second model, where the first training sample includes first feature data of a network device in a site network corresponding to the site analysis device; obtain differential data between the first model and the second model; and send the differential data to the first analysis device. The first analysis device is configured to: send the first model to the site analysis device; receive the differential data sent by the site analysis device; and update the first model based on the differential data to obtain a third model.

Abstract: Disclosed is a real-time intelligent monitoring system for long-distance curved pipe jacking, which includes a pipe jacking mechanism and a working platform, wherein the working platform includes a control console and a main jacking hydraulic oil cylinder, the control console is arranged at one side of the main jacking hydraulic oil cylinder and is electrically connected with the main jacking hydraulic oil cylinder, the pipe jacking mechanism includes a pipe jacking machine, a curved jacking pipe and a jacking pipe, an arcing assembly is arranged inside the curved jacking pipe, a soil settlement monitoring assembly is arranged at the top of the jacking pipe, and laser induction assemblies are arranged inside the pipe jacking machine, the curved jacking pipe and the jacking pipe correspondingly.

Abstract: A soil solidification material based on solid waste and bioenzyme, and a preparation method thereof are disclosed. The soil solidification material is composed of the following components in parts by weight: recycled aggregate 22-35 parts, steel slag 20-30 parts, high-calcium fly ash 16-24 parts, the bioenzyme 5-15 parts, an inorganic adsorbent 10-18 parts, an organic adsorbent 8-20 parts, industrial waste gypsum 25-35 parts, an activator 20-30 parts, sodium citrate 1-3 parts, and slaked lime 0.02-0.2 parts. The present disclosure adopts the recycled aggregate, the steel slag, the industrial waste gypsum and the high-calcium fly ash as the main components of the soil solidification material to reduce the cost. The soil solidification material of the present disclosure prepared by optimizing the proportion is capable of significantly improving the engineering properties of the soil or the mixed contaminated soil, and has significant economic and environmental benefits.

Abstract: This application discloses a model training method, apparatus, and system, and belongs to the AI field. The method includes: receiving a machine learning model sent by a first analysis device; and performing incremental training on the machine learning model based on a first training sample set, where feature data in the first training sample set is feature data from a local network corresponding to a local analysis device. In this application, a problem that the machine learning model obtained through offline training cannot be effectively adapted to a requirement of the local analysis device is resolved. Embodiments of this application are used to predict a classification result.

Abstract: A video quality assessment method and device are provided. The video quality assessment method includes: obtaining a to-be-assessed video, where the to-be-assessed video includes a forward error correction (FEC) redundancy data packet; when a quantity of lost data packets of a first source block in the to-be-assessed video is less than or equal to a quantity of FEC redundancy data packets of the first source block, generating a first summary packet for a non-lost data packet of the first source block, and generating a second summary packet for a lost data packet of the first source block; and calculating a mean opinion score of video (MOSV) of the to-be-assessed video based on the first summary packet and the second summary packet. The MOSV calculated according to the method is more consistent with real video experience of a user, so accuracy of video quality assessment can be improved.

Abstract: A label determining method includes: obtaining a target feature vector of a first time series, where a time series is a set of a group of data arranged in a time sequence; obtaining a similarity between the target feature vector and a reference feature vector in a reference feature vector set, where the reference feature vector is a feature vector of a second time series with a determined label; and when a similarity between the target feature vector and a first reference feature vector is greater than a similarity threshold, determining that a label corresponding to the first reference feature vector is a label of the first time series, where the first reference feature vector is a reference feature vector in the reference feature vector set.