39results about How to "Improve discovery efficiency" patented technology

The invention relates to the technical field of biology, in particular to a preparation method and application of an anti-human MUC1 antibody, and provides a recombination system which utilizes an in-vitro B cell culture technology, uses ELISA (enzyme-linked immunosorbent assay) to detect the expression condition of the antibody, performs flow detection on the binding capacity level with cells and performs antibody expression and assembly through an expression vector. The monoclonal antibody with high specificity and strong affinity is screened out, and the immunogenicity is reduced on the basis that the high affinity combined with the antigen is reserved through humanized transformation, so that the monoclonal antibody is favorably applied to immunotherapy of a human body; the anti-human MUC1 antibody prepared by the invention plays an important role in immunotherapy of tumors, and solves the technical problems of insufficient specificity and lower affinity of the MUC1 antibody in the prior art.

The invention discloses an object group identification method and related equipment. The method comprises the following steps: acquiring operation content information of a plurality of content publishing objects in at least one dimension; according to the operation content information, aggregating the content publishing objects to obtain a primary object group; for each primary object group, mining social relation data corresponding to each content publishing object in the primary object group so as to mine a target social association object having an influence on the primary object group; and combining the primary object groups according to the target social association object and the abnormity degree of the content publishing objects in the primary object groups to obtain a potential abnormal target object group. The method can be better suitable for an organized team discovering anomaly detection scene, the discovery efficiency of the abnormal object and the recall rate of the abnormal object are improved, and therefore the detection range of the abnormal object is widened.

The present application discloses a computer network security analysis method based on big data, which relates to the field of network security, including: collecting user behavior data and interaction data; preprocessing the collected user data set; using a federated learning architecture, taking the preprocessed user data set as a training sample, training a machine learning model locally on the user side for user status analysis; uploading the parameters of the trained machine learning model to a cloud server, performing global aggregation on the cloud service, and obtaining a global machine learning model; based on the global machine learning model and interaction data, using an unsupervised learning method based on anomaly detection to perform security analysis on the user's computer network behavior. In view of the low network security efficiency existing in the prior art, the present application performs real-time analysis of user status through a local BiLSTM neural network model on the user side, and at the same time, uses a federated learning architecture to perform global aggregation on the cloud, etc., thereby improving the efficiency of analysis.

The invention discloses a booster station monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. Collecting and recording events occurring in the booster station according to a preset data collection device; calling a corresponding preset event processing program according to the event type, and processing the event; and pushing the event, the preset event processing program and the event processing result according to a preset mode. The preset data acquisition device is used for automatically acquiring and recording events occurring in the booster station, wherein the events comprise data exception and equipment faults. And the system calls a corresponding preset event processing program according to the event type, processes the event, and pushes the event, the processing program and a processing result according to a preset mode. According to the automatic monitoring and processing mechanism, the fault finding and processing efficiency of the booster station is greatly improved, the requirement of manual intervention is reduced, and stable operation and safety of the system are ensured.

The present application belongs to the field of geothermal energy development and utilization, bridge engineering, and deicing and snow melting technology, and proposes a heat exchange pipe maintenance and intelligent operation and maintenance control method for an energy pile active bridge deck deicing and snow melting system, which comprises an energy pile active bridge deck deicing and snow melting federated learning operation and maintenance control model and a heat exchange pipe maintenance device based on electromagnetic induction principle; the energy pile active bridge deck deicing and snow melting federated learning operation and maintenance control model preliminarily judges and makes alarm positioning, and the heat exchange pipe maintenance device based on electromagnetic induction principle carries out fine repair work; the damaged point is repaired by automatic repair agent or the inner layer pipe is unscrewed. The heat exchange pipe maintenance device based on electromagnetic induction principle comprises a double-layer intelligent heat exchange pipe structure, a micro magneto-electric sensor, a cable storage tray, a data automatic acquisition instrument and a control end. The present application realizes fine control management and early warning of the energy pile active bridge deck deicing and snow melting system, accurately positions and repairs the damaged point, globally and accurately controls the snow melting system, and improves the deicing and snow melting efficiency.

The invention relates to a cluster address list acquisition method and device, computer equipment, a medium and a product. The method comprises the following steps: acquiring internet protocol addresses of a plurality of service host machines; performing communication connection processing on each service host machine according to each internet protocol address and a pre-obtained minimum threshold value of available connection number to obtain an available address list; and performing periodic keep-alive detection processing based on the available address list to obtain a target cluster address list. According to the invention, communication connection processing is carried out on the service host machine according to the internet protocol address and the minimum threshold value of the available connection number, the available address can be quickly screened out, and the address discovery efficiency is improved. And after the available address list is obtained, periodic keep-alive detection processing is performed, so that the availability of the address can be monitored in real time, and the accuracy and reliability of the address list are greatly improved.

The application provides a kind of monitoring area abnormal behavior early warning system, including camera, physiological monitoring intelligent wristband, sensor module, data analysis module and abnormal early warning module;Among them, when the camera collects the behavior data of the prisoner in the monitoring area, it can use local fuzzy method to blur the bathroom area and process the blurred shooting, so as to effectively balance the privacy protection and safety supervision demand;Physiological monitoring intelligent wristband and sensor are used to collect physiological data of prisoners and environmental data in the monitoring area respectively, to provide auxiliary basis for abnormal analysis of behavior data by data analysis module, so that it can timely and accurately identify abnormal events, such as environmental abnormal events, personal injury events, psychological abnormal events and bathroom abnormal events, etc.;Abnormal early warning module can evaluate the risk level of the abnormal event that has occurred, and trigger the corresponding early warning notification, so that the on-duty personnel can timely intervene the abnormal behavior of the prisoner.

A mechanical equipment electric spark monitoring method based on the voiceprint technology comprises the following steps that S1, for each area, terminal equipment collects voiceprint signals, vibration signals and temperature in a preset time period through a sound pickup, a vibration sensor and an infrared temperature measurement camera; s2, the terminal equipment determines wave beams and temperatures in a preset time period according to the voiceprint signals, the vibration signals and the temperatures corresponding to all the areas; s3, the terminal equipment determines an oscillogram in a preset time period according to the wave beam and the temperature; s4, the terminal device determines a sound pressure level, a peak value, a waveform factor and a vibration frequency in a preset time period according to the oscillogram; and S5, when the terminal equipment finds that the voiceprint and the vibration are abnormal, an infrared temperature measurement camera is turned on to carefully observe a specific part, and temperature analysis is carried out on the area. The invention provides a mechanical equipment electric spark monitoring method based on the voiceprint technology. Real-time online detection of electric sparks of mechanical equipment is achieved through the voiceprint recognition technology.

The present invention relates to an anti-CD28 nano antibody, a method for screening CD28 nano antibodies based on a natural library and an application thereof, and belongs to the field of biotechnology. The anti-CD28 nano antibody of the present invention is composed of a heavy chain, and the heavy chain includes three complementary determining regions, namely CDR1, CDR2 and CDR3; the amino acid sequence of the CDR1 is shown in SEQ ID NO:3; the amino acid sequence of the CDR2 is shown in SEQ ID NO:4; the amino acid sequence of the CDR3 is shown in SEQ ID NO:5. The present invention obtains a nano antibody targeting CD28 through an alpaca nano antibody natural library and phage display technology, which can specifically recognize CD28 and has application prospects for the preparation of tumor therapeutic drugs and tumor detection.

This invention discloses a Chlorella heptapeptide TGPLGSR with multi-target lipid-lowering activity, its preparation method, and its applications. The amino acid sequence of this heptapeptide is Thr-Gly-Pro-Leu-Gly-Ser-Arg. The preparation method includes: performing ultraviolet and electroporation combined mutagenesis on wild-type Chlorella proteoglycans to obtain a high-protein-content mutant algal strain; obtaining algal protein through fermentation and synergistic extraction and purification with alcohols; directionally digesting the protein with alkaline protease, followed by enriching the active peptide components through ultrafiltration and gel chromatography; and finally, screening the heptapeptide using liquid chromatography-mass spectrometry (LC-MS), computer-aided prediction, and molecular docking techniques. This heptapeptide exhibits potent inhibitory activity against pancreatic lipase and can dose-dependently reduce the accumulation of triglycerides and cholesterol in 3T3-L1 cells. Its mechanism involves multiple target pathways, including inhibition of MMP-9, activation of AMPK phosphorylation, and downregulation of PNLIP, and it can be used to develop lipid-lowering functional foods or health products.

The application relates to the technical field of data storage and processing, and discloses a stock right penetration method based on bidirectional search, a terminal and a storage medium. The method constructs a stock right graph structure: based on original stock holding data, a directed graph is constructed; a vertex set represents an institution entity, and an edge set represents a stock holding relationship between institutions; the weight of an edge in the stock right graph represents a stock holding proportion between institutions, and a time stamp information is additionally attached to the edge to record the timeliness of the stock holding relationship; graph structure cleaning: deleting an unweighted edge in the stock right graph, detecting and eliminating a circular stock holding; executing bidirectional penetration search: for any given starting point and ending point in the stock right graph, initiating a forward search from the starting point to obtain a forward path, initiating a reverse search from the ending point to obtain a reverse path, and when the forward search and the reverse search meet at a vertex, the reverse path of the forward path and the reverse path are combined, so that a complete stock holding link is obtained. The application can effectively realize stock right penetration between institutions.

The invention discloses a PCN efficient routing protocol based on node stability, which comprises the following steps of: dividing PCN nodes into neighbor nodes, landmark nodes and beacon nodes, and constructing a routing table to store routing related information of the three types of nodes; after a routing table is initialized, when a transaction request exists in a network, a multi-path search algorithm is used to discover a feasible payment path from a source node to a sink node, and an alternative path set is obtained; and for all feasible payment paths in the alternative path set, according to historical transaction data and historical transaction weights of channels on the payment paths, calculating path scores by using a scoring function, and selecting a path with a high path score as a final payment path. According to the method, the node distance and connectivity characteristics in the PCN and the stability of the nodes are integrated, so that the transaction success rate of the PCN can be improved.

The invention discloses a community discovery method and device based on balanced label propagation, and the method specifically comprises the steps: constructing a membership network according to the data of a social network; for the nodes with the degree value larger than 1 in the link list structure, node importance is calculated for each node by using node similarity and degree centrality, node labels and diffusion marks of the nodes are initialized, the node labels are updated according to the node importance, the two adjacent nodes with the highest similarity obtain the same labels, and the nodes with the highest similarity are updated. Selecting nodes of which the importance nodes are greater than a threshold value as initial core nodes, and performing label diffusion in a balance diffusion mode; for the nodes of which the degree values are equal to 1, neighbor labels of the nodes are directly distributed to the corresponding nodes; label selection is carried out according to the comprehensive influence among the communities, so that each node finds the most suitable label; and discovering a final community through rapid merging. The method is high in convergence speed and stable and accurate in result.

The invention provides an epoxy resin formula reverse design system based on iterative optimization and interpretable prediction, and the system comprises a prediction oracle module which is used for receiving at least one candidate polymer formula, and calculating and outputting at least one predicted mechanical performance; the generation engine module is used for receiving a reference formula of epoxy resin and at least one optimization target, generating and outputting at least one candidate polymer formula, and generating an explanation text of the successful candidate polymer formula; the feedback controller module is used for sending a reference formula, an optimization target and an explanatory prompt of a successful candidate polymer formula to the generation engine module, sending the candidate polymer formula to the prediction oracle module, and comparing the predicted mechanical performance with the optimization target. And controlling the generation engine module and the predictive oracle module to execute an iterative closed-loop optimization process. According to the invention, an independent, explainable and improved epoxy resin formula design process is realized, and the discovery efficiency of the epoxy resin formula is accelerated.

The application discloses an anti-glyphosate EPSPS protein and application thereof. The amino acid sequence of the EPSPS protein coded by the gene is shown as SEQ ID NO. 2, the nucleotide sequence optimized for tobacco codon is shown as SEQ ID NO. 3, and the EPSPS protein is fused with a chloroplast signal peptide. The gene is introduced into Nicotiana benthamiana by an agrobacterium-mediated method, and the obtained transgenic plant shows extremely high glyphosate resistance and can tolerate a concentration of up to 36000 mg / L, which is significantly better than that of a traditional CP4-EPSPS transgenic plant. The gene is screened from microorganisms by using artificial intelligence assisted evolution analysis, structure prediction and semantic clustering, and has the characteristics of high-efficiency expression and strong resistance, and can be widely applied to herbicide-resistant breeding of various crops, thereby reducing production cost and environmental risk.

The invention relates to a method and device for identifying potential quality hazards of an optical cable line, and belongs to the technical field of inspection, and the method comprises the steps: registering unmanned aerial vehicle information to an unmanned aerial vehicle platform, and enabling the unmanned aerial vehicle platform to transmit the unmanned aerial vehicle information to an optical network platform; updating the route state of the inspection route of the optical network platform; newly building a tour-inspection plan and generating tour-inspection points; generating a work order according to the inspection plan, sending the work order to an inspection route worker, and after the inspection route worker reaches a preset range of the inspection route, controlling the unmanned aerial vehicle to fly according to the inspection route for inspection and collection; the unmanned aerial vehicle sends a collection result to the unmanned aerial vehicle platform, and the unmanned aerial vehicle platform sends the collection result to the optical network platform in real time; after the optical network platform receives the inspection point image in the collection result, a pre-trained model is called to recognize and judge whether line quality hidden danger exists in the inspection point image or not; if yes, potential quality hazard early warning information is generated; and quality hidden danger early warning information is sent to management personnel. According to the invention, the inspection efficiency and safety are improved.

This application discloses a method for designing high thermal conductivity aluminum-silicon alloys based on machine learning models, relating to the field of metallurgical materials technology. The method includes: constructing an original dataset of aluminum-silicon alloys containing alloy composition, process parameters, and thermal conductivity properties; preprocessing and feature filtering the dataset to obtain key features affecting thermal conductivity; training several machine learning models based on these key features and using the coefficient of determination as a preliminary screening indicator; further screening using model performance indicators; constructing a final thermal conductivity prediction model through model fusion technology; finally, predicting the thermal conductivity of the virtual alloy composition, selecting high thermal conductivity alloy formulations based on the prediction results, and conducting experimental verification. This application solves the problems of traditional alloy design relying on trial and error, long development cycles, and insufficient prediction accuracy, achieving efficient and accurate prediction of the thermal conductivity of aluminum-silicon alloys, and providing an effective means for the intelligent design and development of high-performance thermally conductive materials.

The invention discloses an elevator water immersion internet-of-things wireless monitoring system, and belongs to the technical field of elevator internet-of-things monitoring. The elevator water immersion internet-of-things wireless monitoring system comprises an elevator shaft, an elevator runs in the elevator shaft, far infrared cameras are arranged on the outer walls of the periphery of the elevator, and photos on the wall of the elevator shaft are shot in real time; the temperature of a water immersion point is lower than the temperature of the periphery of the water immersion point, the water immersion point on the shaft wall of the elevator shaft can be found in time, and the position of the water immersion point on the shaft wall of the elevator shaft can be sent outwards through the wireless internet of things. Sundries covering the upper portion of the elevator shaft bottom water outlet can be cleaned in time, the discovery efficiency and convenience of water immersion points of the elevator shaft wall are improved, and the water drainage effect of the elevator shaft bottom is improved.

The invention discloses an open world target detection category discovery method based on semi-supervised contrast clustering. The method comprises the following steps: acquiring an original data set of the open world and a new data set of the open world; constructing an open world target detection category model based on semi-supervised contrast clustering for identifying known categories of the open world targets and clustering and identifying unknown categories of the open world targets; based on the training data in the original data set of the open world and the training data of the new data set of the open world, training an open world target detection category model based on semi-supervised contrast clustering to obtain a trained open world target detection category model based on semi-supervised contrast clustering; and inputting test set data in the new data set of the open world into the trained open world target detection category model based on semi-supervised contrast clustering to realize recognition of a new target category of the open world. The method provided by the invention can adapt to newly appearing object categories in a dynamic environment.

The invention discloses a mountain forest fire prevention early warning method and system, and belongs to the technical field of forest fire prevention. The method comprises the following steps: acquiring patrol data; early warning of high-temperature fire is carried out; early warning of foggy fire is realized; and fire in sunny days can be warned. The method comprises the following steps: determining an area of which the temperature is not higher than a set temperature threshold value, obtaining current meteorological monitoring information, judging whether fog exists or not, if so, monitoring a forest in real time by using high-definition fog-penetrating imaging equipment, obtaining a monitoring image, analyzing a foggy fire index, and if the foggy fire index exceeds the set threshold value, determining whether the foggy fire index exceeds the set threshold value. And if yes, triggering foggy fire early warning, and if not, not carrying out early warning, so that the probability of fire existence under the foggy condition is judged, the probability of analyzing the foggy fire in combination with the manual patrol result and the forest monitoring image acquired by the high-definition fog-penetrating imaging equipment in the foggy condition is achieved, and the problem that in the prior art, under the dense fog weather condition, the foggy fire early warning cannot be carried out in the foggy condition is solved. And the fire risk cannot be effectively identified.

The invention provides a method for detecting fine-grained network assets, which comprises the following steps of: acquiring network asset clue data of a target fine-grained object, and detecting any fine-grained network asset, comprising a network asset detection main node and a plurality of network asset detection distribution nodes which are deployed in different areas and are connected with the network asset detection main node, and a related database is updated in the detection process; the network asset active detection method has the advantages that the network asset active detection is more targeted to a detection target, the detection packet can be customized and constructed to detect the detection target, the accuracy is high, the probe deployment is more flexible, the generalization ability of the model is improved, the burden of manual labeling is greatly reduced, the model can better adapt to a continuously changing data set, and the detection efficiency is improved. And the network assets are determined through the trained preset model, so that the network asset identification efficiency is improved, and the network asset identification accuracy is improved.

The present application belongs to the field of red imported fire ant prevention and control technology, and particularly relates to a red imported fire ant food bait, a preparation method and application thereof. The present application provides a red imported fire ant food bait, which is composed of energy main material and auxiliary material; the energy main material is composed of the following components with the weight content: insect protein powder 50-70%, corn flour 5-20%, peanut oil 9-11%, fish meal 9-11% and sucrose 9-11%. The present application also simultaneously provides an attractant matched with the above-mentioned red imported fire ant food bait. The present application can increase the discovery efficiency of foraging workers of red imported fire ants on the bait, further increase the recruitment behavior of the workers, attract more workers, and has good comprehensive trapping effect.

The invention relates to a commodity shopping guide method and device, equipment and medium in the technical field of e-commerce, and the method comprises the steps: responding to a shopping guide conversation event between a user and an independent station shop customer service, and obtaining an initial text describing the current purchase intention of the user; when it is detected that the specific degree of the current purchase intention described by the initial text does not reach the standard, determining a preference feature data set matched with the initial text based on an interaction behavior sequence of a user; recalling a plurality of shopping guide recommended commodities matched with the initial text, and performing preference priority sorting on the shopping guide recommended commodities based on the preference feature data set to obtain a commodity recommendation list; and pushing the commodity recommendation list to the user so as to display the shopping guide recommended commodities in the list to the user. According to the invention, the customer service of commodity shopping guide is provided for the user, the shopping experience of the user can be greatly improved, and the achievement of commodity transaction is promoted.

The application relates to a network space knowledge extraction method and device based on rule-enhanced prompt learning, which comprises the following steps: acquiring text data to be extracted in a network space security field and a prompt input; splitting the prompt input into a subject prompt, a relationship prompt and an object prompt; connecting sub-prompts of a conditional function related to an ontology rule by using a logical rule with an and normal form to obtain a task-specific prompt for the text to be extracted; performing network space knowledge extraction on the text data to be extracted by using the task-specific prompt and a pre-trained language model trained to output entities and relationships of a current task in the network space security field; and using the entities and relationships to determine threat intelligence data in the current network space security field. The application realizes efficient extraction of entities and relationships in the network space security field by using a prompt tuning technology, and improves the efficiency of threat intelligence data discovery and acquisition in the network space security field.

The present application relates to the technical field of small molecule peptides, in particular to a yak bone anti-aging peptide TGPPGPSGI targeting MMP-1 and application thereof.The amino acid sequence is shown as SEQ ID NO:1.The anti-aging peptide TGPPGPSGI obtained in the present application can be applied in the preparation of health products, cosmetics and food additives.The present application successfully screens and verifies the yak bone source bioactive peptide TGPPGPSGI with good MMP-1 inhibitory activity, which provides a new natural raw material and theoretical basis for the development of anti-skin aging related products.

The application discloses a kind of software development cooperation method and device based on multi-agent system, it is related to software development technical field.The application is converted into structured semantic representation by demand analysis agent using deep learning and field dictionary joint identification technology, and the semantic gap of artificial analysis is eliminated;Through rule verification agent and component optimization agent collaborative work, based on dependency graph construction, rule engine verification and iterative optimization algorithm, automatically identify and correct the logical conflict between form, process, report, solve the maintenance problem of multi-component collaborative consistency;Through seven agent chain cooperation covers the whole process from demand analysis to deployment preparation, the development task that originally needs artificial serial execution is converted into the automatic flow of inter-agent, realizes the whole process automatic intelligent collaborative development from natural language demand to deployable application model, significantly improves software development efficiency and quality.

The application discloses a multi-data-source automatic acquisition and comparison system, relates to the technical field of data processing and automatic test, and comprises the following steps: a scheduling center generates a task context containing a task identifier and a time range; an intelligent sampler determines a sample set based on a strategy-driven random algorithm and a hash modulo operation; a data extraction agent acquires multi-source heterogeneous data in parallel through a unified interface and encapsulates the multi-source heterogeneous data into a virtual data context; a rule execution engine loads a declarative rule, converts data into standard semantic values, constructs a rule execution topology graph, traverses nodes according to a dependency relationship to execute logical assertions or blockages; and a report generation module outputs a diagnostic report by summarizing checking results and original data snapshots. Through full-link data tracking and topological rule checking, the application realizes accurate automatic comparison of multi-source heterogeneous data consistency in a distributed environment.

The invention relates to the field of Internet, and discloses an equipment opening method, device and equipment, and the method comprises the steps: carrying out the broadcasting in a switch local area network according to a first encryption operation code generated based on a first equipment identifier; after the response device verifies the first encryption operation code, receiving a second encryption operation code sent by the response device; performing security verification on the response equipment according to the second encryption operation code; if the security verification of the response device is passed, establishing an encrypted communication channel with the response device; and performing device opening setting on the response device according to the encrypted communication channel. Through the implementation of the scheme, the unique operation code is generated according to the device identifier of the discovery device, the data content in the device discovery process is simplified, the device discovery efficiency is improved, in the device opening setting process, the discovery device and the response device need to be subjected to two-way verification and establish an encrypted communication channel, and the device discovery efficiency is improved. Therefore, the security of the equipment opening setting is improved.

The technical scheme of the invention discloses a management control method for the number of parking times at an intersection. According to the invention, road electronic police, internet road conditions and traffic signals are integrated to control phase data to automatically calculate the intersection parking times, the management and control automation level of the intersection parking times is improved, the discovery and handling efficiency of congestion alarms is improved, and traffic congestion is reduced.

The application provides a method for discovering and connecting electronic devices and the electronic devices, the method comprising: a first electronic device broadcasting a message by using a first communication technology within a first time period (or a first time window), the first electronic device broadcasting a message by using a second communication technology within a second time period (or the first time window), and the first time period and the second time period overlapping; receiving response information sent by a second electronic device; and establishing a communication connection between the second electronic device according to the communication technology capability supported by the second electronic device. The method provided by the application simultaneously broadcasts or sends messages by using multiple communication technology capabilities (for example, BT, Wi-Fi, NFC, Zigbee, USB, Cellular, etc.) of all communication technology capabilities of the electronic device, meets the requirement of a service on the discovery and connection capability of a device with multiple different technology capabilities under a heterogeneous network condition, and improves the efficiency of device discovery.