137results about How to "Maintain validity" patented technology

The invention relates to the technical field of medical care, in particular to an intelligent query method for a nursing knowledge base, which comprises the following steps of: performing multi-form standardized processing on a nursing problem input by a user, deeply analyzing a query request by utilizing a semantic understanding model, and obtaining an intelligent query result based on an inference algorithm; the method comprises the following steps: automatically selecting related literatures, clinical data and nursing experience data from a nursing knowledge base, generating a preliminary nursing scheme candidate set in combination with a nursing professional knowledge graph, and performing personalized screening and optimization on the scheme by using an intelligent recommendation model in combination with the current illness state, treatment progress and historical nursing data of a patient; the intelligent recommendation model is self-optimized through user feedback, and the nursing scheme recommendation precision is continuously improved. The nursing knowledge base automatically fuses newest medical research results and clinical nursing practice data. The problems that in the prior art, nursing scheme recommendation accuracy is low, updating is not timely, and the individuation degree is insufficient are effectively solved.

The invention provides an advertisement recommendation method and system based on deep reinforcement learning. The method comprises the following steps: receiving a real-time interaction signal of a user, analyzing time sequence characteristics in the real-time interaction signal to extract behavior characteristics of the user, and identifying a contextual model of the user; modeling the interest preference of the user to generate a personalized interest dynamic graph; performing intelligent exploration and decision processing on the optimal advertisement content and the corresponding pushing opportunity to obtain an advertisement recommendation strategy; calculating the optimal pushing opportunity corresponding to the optimal advertisement content from the optimal advertisement content and the corresponding pushing opportunity, and pushing the optimal advertisement content to the user based on the optimal pushing opportunity; establishing a real-time feedback mechanism to obtain an adjusted advertisement recommendation strategy; and performing comprehensive evaluation processing on the advertisement effect of the adjusted advertisement recommendation strategy to generate an advertisement effect evaluation result. According to the technical scheme provided by the invention, the flexibility and efficiency of advertisement recommendation can be improved.

The invention discloses a block chain-based performance-lossless watermark credible traceability method and system. The method comprises the following steps of: embedding extended watermark information based on distribution consistent sampling in a potential space of a generative model to obtain a generation content of an embedded watermark; converting the watermark metadata into a hash value, storing the hash value in a block chain, and executing node trust management and a shared data storage and consensus mechanism; inverting the generated content embedded with the watermark to extract watermark information and calculating a hash value, comparing the hash value with the hash value of the watermark information stored in the block chain, if the comparison is consistent, passing the watermark verification, and if the comparison is inconsistent, failing the watermark verification; and when the watermark verification fails, performing node signature verification, if the node signature verification fails or the data is abnormal, starting an on-chain traceability process, tracking a data generation path according to the watermark metadata, and searching an abnormal node or data transmission point. According to the method, lossless embedding, credible circulation and reliable traceability of watermark information can be realized while high quality of generated content is ensured.

The invention discloses a tunnel brightness control dynamic optimization method, a tunnel brightness control dynamic optimization system, a tunnel brightness control terminal and a tunnel brightness control medium, and relates to the technical field of intelligent traffic. According to the method, the vehicle running estimation state capable of representing the overall condition of a target tunnel can be accurately obtained, then traffic flow and vehicle speed prediction is conducted in combination with the vehicle running estimation state and an ADL model, the overall change trend of single data can be accurately analyzed, and association characteristics between different data can be accurately represented; meanwhile, the illumination brightness target value is solved through a brightness optimization function constructed by considering the coordination effect of the traffic flow and the vehicle speed, and the accurate response of the traffic flow and the vehicle speed which change in real time can be realized from the global perspective, so that the reliability and the timeliness of brightness adjustment are improved.

The invention discloses a production safety accident emergency disposal scheme intelligent generation method and system, and the method comprises the steps: obtaining the spatial-temporal characteristics of historical accident cases, calculating the correlation degree, building an accident prediction network based on the correlation degree, simulating uncertain factors, calculating the similarity between a current accident and the historical cases, determining the prior probability, and carrying out the accident development reasoning. The method comprises the steps of tracing accident hazard degrees of different production links, obtaining an cause chain, generating an emergency resource allocation strategy set by utilizing Markov decision, constructing target function optimization, obtaining an emergency disposal scheme, monitoring production process, equipment state and personnel configuration changes in real time, and dynamically adjusting the emergency disposal scheme to adapt to the changes. According to the method, the historical data, the graph neural network and the Markov decision are combined, accident prediction and emergency resource intelligent allocation are realized, the method can adapt to the change of a production environment in real time, the disposal efficiency and safety are improved, and meanwhile, the method has relatively good interpretability.

The invention provides a high-barrier fresh-keeping low-temperature heat-sealing composite film and a manufacturing process and application thereof, the composite film sequentially comprises a heat-sealing layer, a barrier layer, a reinforcing layer and a surface treatment layer from the inner layer to the outer layer, and the layers are bonded through bonding layers. The heat-sealing layer is prepared from modified polyethylene, polypropylene and a heat-sealing auxiliary agent, and the barrier layer is made of a composite material of nano aluminum oxide, polyvinylidene fluoride and an ethylene-vinyl alcohol copolymer. The enhancement layer is a polyester film, and the surface treatment layer is subjected to corona treatment. The composite film is prepared through a specific manufacturing process, and the specific manufacturing process comprises the steps of preparation of the heat sealing layer and the blocking layer, compounding, curing treatment, surface treatment and the like. The composite film disclosed by the invention has excellent barrier property and low-temperature heat-sealing capability, is suitable for vacuum packaging or modified atmosphere packaging of foods, and effectively prolongs the fresh-keeping period and the shelf life of the foods.

The invention discloses a wireless emergency command broadcasting system and method based on artificial intelligence, and the method comprises the following steps: S1, determining the role of a user in an emergency scene through the wireless identity authentication of terminal equipment; s2, acquiring the specific position of each terminal user through a wireless network in real time, and sensing the surrounding environment information of the user; s3, generating a personalized emergency instruction by using a model based on the combination of the graph attention network and the generative adversarial network; s4, a priority optimization algorithm based on hierarchical reinforcement learning is adopted, and the system dynamically adjusts the priority of the broadcast content; s5, a real-time feedback mechanism is established, and the system dynamically adjusts an emergency instruction and a broadcast strategy according to feedback information of a user through a wireless communication technology; and S6, the emergency instruction is pushed to the user terminal, and optimized pushing is carried out according to the characteristics of different users. According to the method, artificial intelligence and wireless communication technologies are fully utilized, personalized emergency instructions are dynamically generated, and the method has the advantages of accuracy, high efficiency and real-time adaptation.

The invention discloses a venous thrombosis risk assessment method and system based on a large language model and deep learning, and the method and system can comprehensively capture the clinical information of a patient through the comprehensive utilization of multi-dimensional and multi-modal clinical diagnosis and treatment data, and improve the accuracy of risk assessment. An automatic feature extraction and selection technology is realized by applying a large language model, manual intervention is reduced, and the comprehensiveness and accuracy of feature extraction are improved. The introduction of the deep learning model enhances the prediction performance of the model, supports real-time data processing and risk prediction, and realizes the automation and real-time performance of risk assessment. Besides, the model framework supports continuous learning and updating, can adapt to new clinical data and research progress, and keeps advancement and effectiveness of the model, thereby providing high-quality hospitalized patient VTE risk assessment services.

The invention relates to the technical field of data processing, in particular to an intelligent recommendation system fusing big data and AI, and the system comprises a scheme obtaining module which obtains a plurality of target marketing schemes; the scheme analysis module analyzes a plurality of target marketing schemes to determine a plurality of marketing features; the data acquisition module collects a plurality of historical behavior data of a user; the data analysis module analyzes a plurality of historical behavior data to determine user characteristics; the association determination module analyzes association between the user features and the plurality of marketing features based on the initial association AI model, and determines prediction priorities of the plurality of target marketing schemes based on an association analysis result; a recommendation module constructs a user recommendation page based on the predicted priority, and determines target priorities of a plurality of target marketing schemes based on the real-time behavior data of the user; and the feedback module compares a comparison result of the prediction priority and the target priority to adjust the initial association AI model to obtain a target association AI model. According to the invention, the accuracy of personalized marketing scheme recommendation of the user is improved.

The invention discloses a multi-dimensional rumor detection and prevention system based on a large language model, which relates to the technical field of rumor detection and comprises a data collection module, a data preprocessing module, a feature extraction module, a background knowledge integration module, a logical reasoning module, a detection and classification module and a prevention and response module. According to the rumor detection method and system, all aspects of the rumor can be comprehensively considered from multiple angles, the aspects include but are not limited to the content of the rumor, the propagation path of the rumor and the interaction condition between the users, and through the comprehensive analysis, the system can ensure that detection of the rumor covers all related dimensions, so that the accuracy and comprehensiveness of detection are improved, and the detection efficiency is improved. The rumor detection and classification work can be efficiently carried out by utilizing an advanced artificial intelligence technology, and through an intelligent means, the system not only improves the detection efficiency, but also remarkably improves the detection accuracy and the intelligent level, so that the rumor detection is more accurate and efficient.

The invention belongs to the technical field of electromagnetic interference elimination, and discloses a method and system for processing electromagnetic leakage interference of an electromagnetic vibration table, and the method comprises the steps: starting a signal collection and analysis module, monitoring an electromagnetic signal generated in the operation process of the electromagnetic vibration table in real time, and recognizing an interference frequency range; a proper filter is selected or designed based on the identified frequency range through a filter selection and design module; a filter processing unit is utilized to install filters on necessary power lines and signal lines, and interference suppression measures are executed; the test and optimization module is operated, the filtering effect is evaluated, the configuration of the filter is adjusted according to needs, and the electromagnetic interference suppression effect is optimized; and the monitoring and adjusting module is continuously executed to adapt to the change of an experimental environment, so that long-term effective electromagnetic interference control is ensured. The invention provides a solution which is more accurate, effective and flexible compared with the traditional physical shielding, and is suitable for the occasion of carrying out high-precision vibration test on the magnetic sensitive sample.

The invention relates to a fault prediction method and system for an IP network. The method comprises the following steps: collecting network link data; extracting network link characteristics according to the network link data; training a GRU model through the network link features to obtain a prediction model; and inputting real-time network data into the prediction model to obtain a prediction result. According to the invention, the efficiency and accuracy performance of performance monitoring and fault prediction can be improved.

The invention relates to the technical field of functional health care products, and discloses a cordyceps militaris probiotic beverage for regulating intestinal flora balance, the probiotic beverage is composed of the following materials by weight: cordyceps militaris extract; a probiotic strain; inulin; fructo-oligosaccharide; a stevia rebaudiana extract; honey; vitamin and mineral supplements; and the balance of distilled water. Studies prove that bifidobacterium, lactic acid bacteria and lactobacillus acidophilus have positive benefits in the aspect of regulating intestinal flora, growth of beneficial bacteria can be promoted, harmful bacteria can be inhibited, and honey, vitamins and mineral supplements are beneficial to improving the overall taste and improving the immunity of the human body. More nutrition support can be provided for intestinal microflora, the balance of the intestinal flora can be maintained and repaired, and the beneficial effect of screening strains aiming at specific health benefits and specially adjusting the balance of the intestinal flora is achieved.

The invention belongs to the technical field of park monitoring and early warning, and particularly relates to a network early warning method for an ad hoc network or a local area network of a park, which comprises the following steps: collecting network data of different sources in the ad hoc network or the local area network of the park in real time, and preprocessing the collected network data of the park; carrying out topological structure identification on the preprocessed network data, and constructing a graph neural network model; fusing the preprocessed network data of different sources by using a multi-source information fusion technology, constructing an early warning model, and identifying an abnormal mode or a potential risk in the network data; early warning output and response: monitoring the park network in real time by an early warning model, and dynamically adjusting the early warning model by using a gradient descent method; and when the early warning model detects an abnormal behavior or a potential fault, an early warning mechanism is triggered, and corresponding response measures are taken. According to the network early warning method for the ad hoc network or the local area network of the park, the accuracy and the efficiency of park early warning are further improved.

The invention discloses a one-stop human resource outsourcing intelligent service platform system, which comprises a talent pool management module, an interview management module, a project management module, an attendance management module, a salary management module, an intelligent risk management module and a notification and announcement module, the project management module is used for follow-up and management of projects; the attendance management module is used for making and managing attendance strategies; the salary management module is used for calculating and managing personnel salary; the intelligent risk management module is used for intelligent risk assessment, early warning and analysis; according to the one-stop human resource outsourcing intelligent service platform system provided by the invention, a talent retrieval recommendation algorithm based on naive Bayes is proposed to retrieve and intelligently recommend information in a talent pool; and an enterprise risk assessment algorithm based on artificial intelligence is provided to carry out intelligent assessment, analysis and prediction on the enterprise risk.

The invention provides a honey spot anti-aging method and system based on digital twinning. The method comprises the following steps: collecting historical original data of a target network and equipment; constructing an initial digital twinborn model, and training the initial twinborn model according to the historical original data to obtain a trained digital twinborn model; obtaining current original data of the target network and equipment, inputting the current original data into the current original data so as to output an event analysis result corresponding to the current original data, and generating and deploying a honey point according to the event analysis result corresponding to the current original data; judging whether the deployed honey points meet preset conditions of aging honey points or not; and if the preset condition of the aged honey point is met, performing anti-aging operation on the aged honey point. According to the invention, the flexibility, adaptability and resource utilization efficiency of a network security system can be obviously improved.

The invention discloses an intelligent assessment method and system for regional geological disaster risk, and relates to the technical field of intelligent assessment. During operation of the system, various real-time data related to debris flow are acquired by integrating real-time sensors and satellite remote sensing data, original data are preprocessed and stored in a data storage system; based on the collected data, a physical model and a machine learning model are constructed, a debris flow disaster risk index MRI, a rainfall intensity coefficient RIC, a geological vulnerability coefficient GVC and a hydrodynamic pressure coefficient HPC are obtained after calculation, the probability of debris flow occurrence is predicted, and a result is output according to the model. The debris flow disaster risk index MRI is compared with a preset first safety threshold value M and a preset second safety threshold value N, the risk level of debris flow occurrence is evaluated, different areas are managed in a classified mode, debris flow early warning is given out according to real-time monitoring data and risk evaluation results, and automatic emergency response measures are supported.

The invention discloses an AUV (Autonomous Underwater Vehicle) multi-target global path planning method based on a sparrow search algorithm in the field of artificial intelligence and ocean engineering, and the method comprises the following steps: S1, constructing a multi-target optimization model with path length and path safety as the core, and reducing the total length of a path as much as possible while ensuring that the path avoids an obstacle, therefore, a short and safe path is found; s2, determining constraint conditions of path search of the AUV in a complex static environment formed by a plurality of obstacles; s3, solving the multi-objective optimization model established in the step S1 by using a sparrow search strategy; s4, after the algorithm converges, outputting an optimal solution, and drawing an obstacle avoidance 3D schematic diagram and a Pareto frontier map in AUV path planning according to the optimal solution; according to the invention, by improving the sparrow search algorithm and introducing an obstacle avoidance mechanism, the problem of path optimization in a complex underwater environment can be effectively solved, and the navigation efficiency of the AUV and the reliability of task completion are improved.

The invention discloses a smart contract vulnerability detection method, apparatus and device, and a removable storage medium. The method comprises the steps of obtaining a to-be-applied smart contract original code and performing preprocessing; performing code completion on the preprocessed original code of the smart contract by using an LLM model and a GPT model to generate a smart contract completion code; extracting an abstract syntax tree in the intelligent contract completion code, and constructing a control flow graph; and trimming the control flow graph according to the smart contract original code and the abstract syntax tree, and performing mode matching on the trimmed control flow graph based on a preset vulnerability specific mode to generate a vulnerability recognition result. According to the method, firstly, the code snippets are intelligently complemented by utilizing the language model, the complete context information of the code snippets is recovered, and then vulnerabilities possibly existing in the complemented codes are deeply detected in combination with a symbolic execution technology, so that the security of the code snippets can be accurately evaluated, and the security of the code snippets is improved. And the security risk caused by multiplexing the code snippets with vulnerabilities is avoided.

The invention relates to the technical field of fracturing fluids, and discloses a fracturing fluid and a preparation method thereof.The preparation method comprises the steps that cardanol modified polyurethane, modified silicone rubber, hexadecyl trimethyl ammonium chloride, sodium salicylate and water are added into a reactor and stirred, and the fracturing fluid is obtained after stirring is finished. Wherein the quaternary ammonium salt group can reduce the reservoir damage by reducing the hydration of clay on the surface of shale and inhibiting the expansion and migration of the clay, can still keep stable performance at high temperature, and is beneficial to improving the temperature resistance of the fracturing fluid; wherein polyurethane has good temperature resistance, hydrogel is formed through crosslinking, and the hydrogel can still keep stable at high temperature, so that the temperature resistance of the fracturing fluid can be improved; cardanol in the fracturing fluid has good high temperature resistance, and can maintain the stability and effectiveness of the fracturing fluid under a high temperature condition; the silicon rubber structure contains silicon-oxygen bonds, so that the viscosity of the fracturing fluid can be improved, and meanwhile, the fracturing fluid has good anti-shearing capability in a high-temperature environment.

The invention discloses a self-learning fault knowledge management method and system based on artificial intelligence, and belongs to the technical field of equipment fault prediction and management, and the method specifically comprises the steps: obtaining historical fault data, historical maintenance data and sensor data of equipment, preprocessing the obtained historical fault data, historical maintenance data and sensor data of the equipment, including data cleaning, sorting and classification, extracting the features of the historical fault data, historical maintenance data and sensor data of the preprocessed equipment, establishing a fault prediction model, predicting and diagnosing the fault of the equipment, and determining the fault of the equipment. Establishing an equipment fault knowledge base, updating the equipment fault knowledge base by utilizing a self-learning strategy according to the fault prediction and diagnosis result of the equipment, and adding the fault predicted and diagnosed by the equipment into the equipment fault knowledge base for next prediction and diagnosis of the equipment; and automatic learning, updating and optimization of fault knowledge are realized, so that the fault diagnosis and management efficiency of the system is improved.

The invention relates to a speech synthesis system-oriented model watermarking method and device, computer equipment and a storage medium, and the method comprises the steps: constructing an intra-domain watermark triggering sample based on a pre-trained speech synthesis model and a fine-tuned speaker recognition model; constructing a corresponding watermark implantation data set based on the watermark triggering sample; based on a fine-tuned speaker recognition model, implanting the watermark implantation data set into the speech synthesis model to obtain a marked model; and screening out a target watermark triggering sample based on the marking model. Through the method and the device, the problem that the watermark is easy to lose in a model fine tuning process due to the fact that the relevance between the watermark and the speech synthesis main task is not strong in the prior art is solved, strong coupling between the watermark triggering task and the model main task is forced from a data level by utilizing the watermark triggering sample in the construction domain, the robustness of the watermark in the marked model is improved, and the speech synthesis efficiency is improved. And the target watermark trigger sample keeps stable and effective.

The embodiment of the invention discloses a head-up display system control method and device, equipment and a medium. The method comprises the following steps: acquiring image information including eyes of a user, and acquiring an eye region image based on the image information; acquiring an actual projection position of the head-up display system, and establishing a sight line dot matrix corresponding to the eye region image based on the actual projection position; determining pupil position information of the user based on the sight line dot matrix, and obtaining a mapping relation between the pupil position information and the actual projection position; and if it is monitored that the pupil position information changes, determining a target projection position of the head-up display system based on the changed pupil position information and the mapping relationship, so as to control a reflection angle of a reflector of the head-up display system based on the target projection position. According to the embodiment of the invention, the effectiveness and accuracy of information display can be continuously maintained by dynamically adjusting the projection position, the method is suitable for various use scenes and user states, the user experience is improved, and the driving safety is improved.

The invention relates to the technical field of medical treatment, and particularly discloses a traditional Chinese medicine acupoint stimulation sleep improving device which comprises a placing frame, a first power assembly is arranged on one side of the placing frame, a moving block is slidably connected to the placing frame through the first power assembly, a clamping plate is fixedly connected to the top end of the moving block, and a second motor drives a disc to rotate. A disc drives a plurality of stress columns to rotate around the circle center, so that meshing teeth in a kidney-shaped frame are intermittently pushed, the kidney-shaped frame reciprocates back and forth, a plurality of massage blocks are driven to move back and forth on the head of a patient for massage, a third motor drives a convex plate to rotate, and a transmission block drives a mounting plate to move. Therefore, it can be ensured that massage acts on the target acupuncture point more accurately, the treatment effect is improved, meanwhile, continuous pressure and stimulation generated by long-time massage on the same acupuncture point are avoided, the discomfort of the patient is reduced, and the overall comfort degree is improved.

The invention relates to the technical field of computer vision and artificial intelligence, and discloses a product appearance defect detection device based on a multi-modal model, the product appearance defect detection device comprises a base and an image recognition device, the image recognition device has multiple operation modes of vision, infrared and 3D scanning, and an auxiliary support and a support ring frame are respectively mounted at the top and in the middle of the base. According to the product appearance defect detection system and detection equipment based on the multi-modal model, an arranged image recognition device is driven by a corresponding third meshing output part, a second gear sleeve plate and a movable annular plate, and the image recognition device rotates and is adjusted around a composite detection supporting part; according to the invention, the image recognition device is integrated with visual data, infrared data, 3D scanning data and other modal data, so that the whole equipment can capture and analyze product appearance information in more dimensions, and even defects which are sensitive to light or hidden can be accurately recognized.

The invention provides a non-intrusive java type application log desensitization method, and relates to the technical field of data desensitization, a java framework log module method is rewritten and desensitized through a desensitization program, and increased data information is obtained; obtaining log record information, performing preliminary judgment on the log record information, and obtaining judgment passing data according to the preliminary judgment information; analyzing the judgment passing information, performing cyclic judgment on the k value to obtain cyclic judgment information, and performing desensitization processing according to a cyclic judgment result to obtain a final processing result; calculating a desensitization efficiency coefficient, judging the desensitization efficiency, further calculating a desensitization precision coefficient, judging the desensitization precision, and updating the desensitization process data in real time according to a judgment result; and after all cycle judgments are desensitized, obtaining a desensitization completion result, and outputting desensitized or non-desensitized log record information.

An intelligent respiratory training instrument disclosed by the present invention comprises an integrated box, a breathing mask, an electrical stimulation patch and a box body, the inner wall of the breathing mask is fixedly connected with an oral cavity tube in a penetrating manner, the side wall of the box body is fixedly connected with an adjusting tube in a penetrating manner, the inner wall of the adjusting tube is rotatably connected with a spline shaft in a penetrating manner, and the side wall of the spline shaft is fixedly provided with an impeller. An H-shaped plate is fixedly connected to the side wall of the top of the spline shaft, connecting rods are rotatably connected to the inner side walls of the two ends of the H-shaped plate, gravity balls are fixedly installed at the other ends of the connecting rods, a bottom plate is connected to the side wall of the spline shaft in a bonding mode, and pull rods are symmetrically and rotatably connected to the side wall of the bottom plate; the other end of each pull rod is rotationally connected with the adjacent connecting rod, and the bottom wall of the H-shaped plate is elastically connected with the bottom plate through a reset spring. By monitoring the intensity state of gas exhaled by a patient, the intensity state is fed back to the controller in the integrated box to automatically adjust training parameters, so that the optimal training effect is achieved.

The invention discloses an electronic information security storage method and system, particularly relates to the technical field of information storage security, and is used for solving the problem of poor stability and consistency of generating an encryption key by using a PUF (Physical Unclonable Function) under complex and changing environmental conditions in the prior art. Generating a PUF response by using hardware equipment in a controlled environment so as to obtain an initial encryption key; continuously monitoring the stability of the PUF response in the current environment by adopting a quantum decoherence analysis technology based on quantum behavior simulation; environment data around the hardware equipment are collected in real time and compared with a preset environment threshold value, and whether the environment is suitable or not is evaluated; a self-similarity model is constructed through segmented sampling and Hurst index analysis of the PUF response signals, and the stability and consistency of the PUF response signals are further evaluated; and finally, whether the encryption key is generated or not is judged through comprehensive analysis, so that the security of generation and management of the key is remarkably improved.

The utility model relates to the technical field of glass processing transportation equipment, in particular to a glass processing vacuum chuck carrying mechanical arm which comprises a supporting piece and a carrying piece, the supporting piece comprises a bottom plate, a cylinder frame and a sliding frame, the cylinder frame is vertically and rotatably connected to the upper portion of the bottom plate, the sliding frame is horizontally fixed to the top face of the cylinder frame, and the carrying piece is arranged below the sliding frame. The carrying part comprises a hanging bracket, the hanging bracket is arranged below the sliding frame, a vacuum suction cup is horizontally fixed to the lower side of the interior of the hanging bracket, a movable rod frame is horizontally fixed to the outer side of the bottom of the vertical end face of the hanging bracket, an abutting hydraulic rod is horizontally fixed to one end of the movable rod frame, an abutting plate is vertically arranged on the movable rod frame, and a hole seat is horizontally fixed to the top face of the abutting plate; the hole seat is horizontally and slidably assembled on the movable rod frame, and the output end of the abutting hydraulic rod is fixed to the outer wall of the hole seat. The side face of the glass plate is clamped through the abutting-pressing plates, displacement of the glass plate is limited through the abutting-pressing plates, and the glass plate hoisting effectiveness and stability are kept.