145results about How to "Easy way to get" patented technology

The invention discloses a method of comprehensively judging a resident trip mode based on handset signaling data, which belongs to the transport planning and management data analyzing field. A data source is from handset signaling data provided by mobile network service providers. Data cleaning, integrating and position conversion are further performed. A resident trip mode is further judged by mobile space-time path describing and stopover point identifying. The method which can effectively discriminate seven common trip modes including walking, bicycling, routine bus, electric vehicle, self-driving, taxi and rail transit thus acquires trip mode information of residents. A data basis is further provided for fields of special traffic programs, comprehensive traffic programs and intelligent traffic systems of cities, etc.

The invention provides an online detection method of energy consumption information in a machining process of a main drive system of a machine tool. According to the method, real-time data, such as loss power of a mainshaft motor, output power of the mainshaft motor, loss power of a mechanical drive system, cutting power, and the like of energy consumption information of the main drive system of the machine tool can be solved just by measuring the total input power of the machine tool in the production site in the machining process, according to established mathematical models of energy flowsand main energy consumption information of the main drive system in the machining process of the machine tool, and base data, such as no-load power and additional load loss coefficient of the machinetool, which are obtained in advance when a mainshaft is in a machining rotation speed, rated power of the mainshaft motor, rated efficiency of the mainshaft motor, no-load power of the mainshaft motor, and the like. The online detection method can be directly applied to researches, such as acquisition of energy efficiency of the machine tool, efficiency estimation of the machining process, energyconsumption monitoring, energy management and energy saving technologies and has wider application prospect.

The invention discloses a new method for obtaining energy efficiency of a main electromechanical driving system in a machining process of a numerically-controlled machine tool. In the method, according to an energy efficiency mathematical model of the main electromechanical driving system in the machining process of a machine tool, a relation function of no-load power of the machine tool which is prepared in advance stage at one time and the rotating speed and a table function of an additional load loss factor of the machine tool with single-interval or multi-interval rotation speed, as long as input power process data or process curve of a motor of the main driving system of the machine tool in the machining process is recorded, the energy efficiency of the main electromechanical driving system in the machining process of the machine tool can be calculated out from the mathematical model. The method can be used for research and application of solution to a series of problems, such as research on energy consumption and energy efficiency and evaluation on energy efficiency in the machining process of the machine tool, and energy-saving optimization of cutting technology parameters, thereby having extensive application prospect.

The invention provides a mobile terminal and server interactive method which comprises the steps that (100), a mobile terminal obtains a static image; (200), the mobile terminal preprocesses the static image to obtain the preprocessed data; (300), the mobile terminal sends the preprocessed data to a server; (400), the server analyzes the preprocessed data to obtain the analyzed data; (500), the server retrieves a retrieved result relevant to the analyzed data in a database according to the analyzed data; (600), the server feeds back the retrieved result to the mobile terminal; (700), the retrieved result is displayed on the mobile terminal; (800), when a user determines and selects the retrieved result on the mobile terminal, the mobile terminal sends a request message to the server, and the message comprises an identifying message corresponding to the selected retrieved result; (900), the server responds to the request message and sends a further message to the mobile terminal. The invention further provides a mobile terminal and server interactive system for achieving the method.

The invention discloses a three-dimensional wireless sensor network node self-locating method based on a neural network. The three-dimensional wireless sensor network node self-locating method comprises the following steps that firstly initializing a wireless sensor network, secondly establishing a neural network, thirdly extracting training examples for the neural network, fourthly training the neural network through the obtained training examples, fifthly obtaining the actual distance from each unknown node to an anchor node which is not adjacent to the unknown node according to the well-trained neural network, and sixthly obtaining the three-dimensional coordinates of the known node. The obtaining method of the training examples is simple and has strong representative, and the well-trained neural network can better represent the main properties of a geometric structure of the three-dimensional wireless sensor network. The three-dimensional wireless sensor network node self-locating method solves the problem of overlarge estimation error of distance brought by the accumulation system of shortest jumping distances in the locating process of the three-dimensional wireless sensor, and effectively improves the locating precision.

The invention discloses a medical big-data analysis and processing system and method based on the IOT (Internet of Things), and belongs to the technical field of data processing. The big-data analysisand processing system mainly comprises a cloud service platform, a user terminal, a hospital database and a medical platform terminal. The medical big-data analysis and processing method of the invention comprises the steps: data acquisition and transmission, data preprocessing, prediction model constructing, and testing and optimizing of a prediction model. Therefore, the prediction model for indicating the probability of a disease of a predicted object or the probability that the predicted object has a certain disease is obtained, and the IOT transmission of the data information is achievedthrough a communication module. Moreover, the prediction model is obtained based on the convolutional neural network The data source with many correlations and wide influences is inputted, and the data has been preprocessed, which greatly improves the accurate reference value of the prediction results.

The invention provides a stagnation point judging method based on home-work correspondence and time-space kernel clustering. User signaling data and user internet surfing data with high frequency signal triggering and time-space association features in a specified time period are acquired according to sampling requirements; through two turns of home-work correspondence and space-time kernel clustering analysis, a set of coarse-grained time-space stagnation points with the time-space activity characteristics is formed; the obtained time-space stagnation set is subjected to verification and algorithm optimization, and the activity characteristics of special population is analyzed; finally, an OD matrix travel schedule based on the traffic community is formed, thereby providing big data support, which satisfies the characteristics of the time-space travel activity chain, for the traffic planning and traffic demand management. The stagnation point judging method based on home-work correspondence and time-space kernel clustering in the invention combines the advantages of the home-work correspondence and the time-space kernel clustering analysis to finally form a stagnation point sequence with the time-space activity characteristics, further improves the rationality and accuracy of the traffic travel OD matrix and effectively reduces the cost.

The invention relates to an object attitude determination method and device, electronic equipment and a computer medium. The method comprises the steps of obtaining a monocular vision image of an object; inputting the monocular vision image into an attitude determination network, and determining attitude information of the object; W; wherein the attitude determination network is obtained by training a simulation image sample set and a real image sample set. By utilizing the method provided by the embodiment of the invention, the cost of obtaining the sample data can be reduced on the basis ofensuring the high accuracy of the attitude determination network.

The invention relates to a method for determining the shear yield surface and the volume yield surface of geotechnical materials, and relates to the technical field of measuring solid deformation. Inorder to judge stress yield of the geotechnical materials, the shear yield surface is fitted by a quadratic polynomial, and the volume yield surface is fitted by an ellipse and a hyperbola; parametricregression of the shear yield condition of the quadratic polynomial is conducted through a constant average stress triaxial test and a conventional triaxial compression test; parametric regression ofthe volume yield conditions of the ellipse and the hyperbola is conducted through an undrained constant average stress triaxial test and the conventional triaxial compression test; a regression curveof the yield surfaces is drawn according to the shear yield condition, the volume yield conditions and relevant parameters; and according to specific response values of the shear yield condition andthe volume yield conditions in engineering, whether shear yield or volume yield occurs in the geotechnical materials or not is evaluated. According to the method for determining the shear yield surface and the volume yield surface of the geotechnical materials, whether yield of the geotechnical materials exists after stress or not can be judged in engineering, corresponding measures are taken to prevent material damage and collapse accidents.

The invention relates to a natural sericin encapsulated mesoporous silicon nano-carrier and a preparation method and application thereof to the field of tumor treatment. The preparation method comprises the steps of preparing pure sericin solids; preparing mesoporous silicon nano-particles; preparing aminated, formylated or dual-sulfurated mesoporous silicon nano-particles with regular pore passage; preparing drug-loaded aminated, formylated or dual-sulfurated mesoporous silicon nano-particles; preparing a pH / protease or reduction / protease dual-responsiveness sericin / mesoporous silicon composite multifunctional control system. The natural sericin encapsulated mesoporous silicon nano-carrier and the preparation method and the application thereof have the advantages that the operation is simple to perform, the raw materials are simple and convenient to obtain, the cost is low, the universal applicability is high, no special complex equipment is needed and the like. The nano composite system prepared by adopting the method fully utilizes the characteristics of the sericin on the outer layer and the mesoporous silicon nano-particles on the inner layer, has pH / protease or reduction / protease dual responsiveness, has multiple functions of inhibiting tumor cells, monitoring nano-particle positioning and drug release in real time and the like, is high is drug loading capacity, is good in biocompatibility and has a wide application prospect in the field of tumor diagnosis and treatment, especially in the aspect of solving multi-drug resistance of tumors.

The invention provides a feature recognition method for different travel activities based on mobile phone positioning data. The method comprises the steps of carrying out the job-house and life travelpurpose time-space kernel clustering analysis and time-space correlation feature analysis of OD residence points of the mobile phone positioning data, forming different travel activity purpose travelchains with time-space correlation features, and carrying out the pairing of the travel chains; performing verification and algorithm optimization on the obtained time-space stationary point set, performing analysis on crowds with different travel activity target features, and finally forming an OD matrix travel table based on a traffic cell, thereby providing big data support meeting the features of a space-time travel activity chain for traffic planning and traffic demand management. According to the invention, the respective advantages of the time-space activity correlation analysis and the OD matrix generation table are combined to finally form the stationary point sequence with time-space activity target features, so that the rationality and accuracy of OD matrixes of different travel targets of traffic are further improved, and the cost is effectively reduced.

The invention discloses a method for processing a natural plant feed coloring agent. The manufacturing process of the feed coloring agent comprises the following steps of: picking okra mature leaves with the content of lutein and beta-carotene of both over 300mg / kg; crushing the okra mature leaves into yellow green powder, and sieving with a 100-mesh sieve; mixing the yellow green powder, vitamin C and citric acid in a mass ratio of 95-99.8:2.5-0.01:2.5-0.01; and preserving the mixture in a sealed and shaded environment with a humidity of 40 percent and at the room temperature of 2 to 10 DEG C. A plant having high color material content, a good nutrition constituent, a high coloring speed, an obvious coloring effect, a simple acquisition way and a low processing cost is screened from a large number of plant resources, is processed into the natural plant feed coloring agent which has a good coloring effect on skins, fats and yolks of poultry after being processed, belongs to a purely natural green product, ensures the safety and quality of foods and has a good utilization and development prospect as the feed coloring agent for the poultry.

The invention provides a reconstruction method for controlling the pulses through the rotating speed of a rotating valve. After drilling fluid pressure differential phase shift keying signals or drilling fluid pressure quadrature phase shift keying signals which are obtained from a well opening pressure sensor are subjected to signal treatment and pumping pressure interference and noise are eliminated, phase signals reflecting the carrier phase change during drilling fluid pressure differential phase shift keying modulation or phase signals reflecting the carrier phase change during drilling fluid pressure quadrature phase shift keying modulation are obtained through coherent demodulation and anti-cosine calculation, the control pulses of the rotating speed of the rotating valve are reconstructed by conducting derivative operation on the phase signals, and the reconstructed control pulses of the rotating speed of the rotating valve are not influenced by the phase error during coherent demodulation; and logical judgment is conducted on the amplitude of the constructed control pulse of the rotating speed of the rotating valve according to the data coding rule, the code element state represented by the pulses is determined, data codes are arranged according to the occurrence time sequence of the pulses, and decoding of the drilling fluid pressure differential phase shift keying signals or the drilling fluid pressure quadrature phase shift keying signals is achieved.

The invention relates to an air conditioning device and a method used for judging whether an operating state of the air conditioning device is normal or not. The method comprises the following steps of obtaining an air inlet temperature and an air outlet temperature of the air conditioning device after a compressor of the air conditioning device stably operates for first preset duration with highest operating frequency permitted under the current working condition; calculating an absolute value of the difference between the air outlet temperature and the air inlet temperature; and judging thatthe operating state of the air conditioning device is normal when the absolute value of the difference between the air outlet temperature and the air inlet temperature is greater than or equal to a preset temperature difference threshold value. The heating and refrigerating effect of the air conditioning device can be directly reflected with the air outlet temperature when the compressor stably operates with the highest operating frequency, and therefore, the absolute value of the difference between the air outlet temperature and the air inlet temperature can accurately and timely reflect a refrigerant amount condition in a refrigerating system of the air conditioning device, and accuracy and timeliness of judging are improved. Meanwhile, an obtaining way for the air inlet temperature andthe air outlet temperature is very simple, the internal structure of the air conditioning device is simplified, and the cost is reduced.

The embodiment of the invention discloses a timber defect sample obtaining method and apparatus, an electronic device and a storage medium. The method includes the following steps: obtaining data of qualified timber samples; obtaining defect characteristic images on the basis of the data of the qualified timber samples, wherein the defect characteristic images are obtained from an existing defecttimber sample database; and combining the defect characteristic images and the data of the qualified timber samples together to obtain data of defect timber samples that have the same timber categorywith timber in the qualified timber samples. Through the above way, problems that a trained artificial intelligence model cannot identify timber defects and the identification precision is low due toloss of defect timber samples in a training initial stage of the artificial intelligence model are overcame, defect timber sample data obtaining ways are simplified, and costs are saved.

The invention discloses an independent automatic meter reading device and a meter reading system using the device. The automatic meter reading device comprises a processor which is respectively electrically connected with an image acquisition unit, a short-distance wireless transmitting and receiving module and a remote-distance wireless transmitting and receiving module. After acquiring a degree image, the meter reading device centralizes data through a short-distance wireless transmission network, and transmits the data to a back-end device through a remote-distance wireless transmission network. Moreover, an image identification unit is arranged on the meter reading device or the back-end device and used for executing identification and reading of the data image. Therefore, the automatic meter reading device and the meter reading system using the device can achieve the efficacies of automatically reading the degree data and automatically transmitting the degree data to a remote-end device without the necessity of replacing a meter and an energy pipeline.

The invention provides a method for achieving a high-speed channel through a self-accumulating propping agent. By means of the material of the self-accumulating propping agent, a channel fracturing technology is completely implemented from the seam end to a seam opening, and a real channel fracturing technology is formed. According to the method, the advantages of the self-accumulating propping agent are achieved, the defects of traditional channel fracturing improvement are overcome, the effect that a high-flow conductivity channel is formed through channel fracturing is achieved better, theseam opening is supported, and the flow conductivity is improved, backflow of the propping agent is reduced; and silt is gathered and concreted in a two-time aggregation manner, new propping agent masses are formed, construction is easy and convenient, and a new output-growing technology guided by the self-accumulating propping agent is formed.

The embodiment of the invention provides a vehicle battery management method and system, a vehicle and a server. The battery management method applied to the vehicle comprises the steps of collectingbattery data of the vehicle, and sending the battery data to a server; receiving a fault processing strategy pushed by the server according to the battery data; and outputting the fault processing strategy to a user, or controlling an execution mechanism of the vehicle to execute an operation corresponding to the fault processing strategy according to the fault processing strategy. According to the embodiment of the invention, real-time storage and acquisition of the vehicle battery data can be realized, the acquisition mode of the battery data is flexible and simple, and professional equipment and professionals are not needed.

The invention provides a laser radar transport flux computing method and a laser radar transport flux computing device. The laser radar transport flux computing method includes acquiring extinction coefficients of particulate pollutants collected by laser radar as well as reanalysis-mode meteorological data including wind-field data and humidity data; subjecting the extinction coefficients to humidity correction according to the humidity data in the reanalysis-mode meteorological data so as to obtain dry aerosol extinction coefficients; computing particulate pollutant vertical profiles according to the dry aerosol extinction coefficients and ground monitoring particulate pollutants; computing laser radar transport fluxes according to the particulate pollutant vertical profiles and the wind-field data of the reanalysis-mode meteorological data. The laser radar transport flux computing method has the advantages that the reanalysis-mode meteorological data are used for humidity correction of the extinction coefficients and laser radar transport flux computation, are acquired simply at a quite low cost and comprise the wind-field data and the humidity data which are both high in precision, and accordingly the whole laser radar transport flux computing method is low in cost and high in popularization degree.

The invention discloses a road traffic state identification method, which comprises the following steps: generating a coverage simulation map layer of a specific area through coverage forecast simulation; carrying out overlay analysis on the coverage simulation map layer and a road to be identified to obtain a base station cell switching sequence of the road to be identified; determining movement trace sequence of each user according to the obtained mobile phone signaling data of each user within a specific time period in the specific area; calculating similarity between the movement trace sequence of each user and the base station cell switching sequence of the road to be identified, and recording the number of users, the similarity of which is larger than a preset threshold value; and identifying the traffic state of the road to be identified with the specific time period according to the number of the users. The invention also provides a road traffic state identification device. The road traffic state identification method and device can realize traffic state high-precision identification of the road to be identified; and computation complexity is low, and cost is low.

The invention provides a method and product for acquiring plant alkaloid and an aroma substance in coffee or tea by heating suction. The product comprises a raw material core and a heating device; theraw material core is formed by machining the coffee or the tea used as a main raw material; and the heating device mainly comprises a power supply, a controller, a heating cavity and a shell. When the product is in use, the raw material chip is placed into the heating cavity, the controller controls the power supply to supply power to the heating cavity, the heating cavity heats the raw materialcavity, the plant alkaloid such as caffeine and the like, the aroma substance and an atomizing agent are separated from the raw material chip due to heating so as to form steam fog together, and the steam fog is directly sucked into the mouth of a user in a suction mode so as to achieve a refreshing effect and generate pleasant satisfaction. Compared to a conventional method for drinking by brewing and the like, the method and product for acquiring the plant alkaloid and the aroma substance in the coffee or the tea by heating suction, which are provided by the invention, have the characteristics of no limitation to brewing utensils, simple acquisition mode, repeated use, aromatic flavor, good refreshing effect and the like, and have good application prospect.

The invention relates to the technical field of communication, and provides an information prompting method and a mobile terminal. The method includes the steps of detecting a residual storage space value of the mobile terminal, determining a target voltage value corresponding to the residual storage space value, and outputting an electric signal of the target voltage value to an electrochromism assembly, wherein the electrochromism assembly displays the color for indicating the residual storage space value when the electric signal of the target voltage value is input. Thus, the mobile terminal can display the residual storage space of the mobile terminal to a user in real time, the user does not need to manually operate the mobile terminal to check the residual storage space, and the information obtaining mode is simple.

The invention provides a preparation method and application of a nitrogen-doped graphene-loaded carbon nitride composite material for activating persulfate. The preparation method comprises the following steps: S1, preparation of raw materials: selecting the commercial graphene, the melamine and the urea; S2, mixing: uniformly mixing commercial graphene, melamine and urea; S3, calcining: putting the commercial graphene, the melamine and the urea which are uniformly mixed in the step S2 into a tubular furnace in a nitrogen atmosphere, conducting calcining with a temperature controlled to be 500to 600 DEG C and a heating rate controlled to be 3-8 DEG C / min, allowing the temperature to be constant for 220-250 min, and performing cooling to room temperature in the nitrogen atmosphere so as toobtain the nitrogen-doped graphene-loaded carbon nitride composite material g-C3N4 / rGO-N for activating persulfate. The g-C3N4 / rGO-N has an efficient effect on removal of novel pollutants such as endocrine disruptors BPA and antibiotics CIP and removal of conventional dyes AO7 and OG, the dosage of a novel oxidation system catalyst and an oxidizing agent is small, and cost is low.

The invention relates to a neural network-based spacecraft attitude control nozzle fault intelligent diagnosis system and method. The system comprises a spacecraft attitude control nozzle fault data generation module and a fault diagnosis module; the fault data generation module is used for obtaining the fault information of a spacecraft attitude control nozzle as well as a corresponding spacecraft attitude error curve and the output curve of a controller during a spacecraft attitude control nozzle fault; with the fault data generation module adopted, a large amount of fault information can beobtained so as to be used for the training of the fault diagnosis module; the fault diagnosis module is used for the fault diagnosis of the spacecraft attitude control nozzle; the fault diagnosis module is based on a convolutional neural network technology; the output information of the fault diagnosis module is the working state of the attitude control nozzle; and the fault type of the spacecraft attitude control nozzle can be determined through the fault diagnosis module. With the neural network-based spacecraft attitude control nozzle fault intelligent diagnosis system and method of the invention adopted, the fault type of the spacecraft attitude control nozzle can be diagnosed accurately through the fault diagnosis module; the reliability of a spacecraft attitude control system is enhanced; and the fault resisting capacity of the spacecraft attitude control system is improved.

The invention provides a training method of the early warning model of primary liver cancer. According to the training method, a primary liver cancer early screening model is established by utilizinga machine learning algorithm on the basis of clinical examination data. The method comprises the following steps that: (a) carrying out data preprocessing on the obtained clinical examination data; (b) carrying out data set division on a preprocessed data set; (c) training a model according to divided data sets; and (d) evaluating and verifying the performance of the classification model. According to the screening model, the clinical examination data are utilized; on the basis of actual clinical requirements, a threshold value is selected through the performance index curve of the optimizedmodel so as to perform test verification, so that primary liver cancer clinical early warning can be carried out; conditions are provided for the early successful diagnosis of liver cancer; and the life quality of a patient is improved.

The invention discloses a rainfall-type landslide risk three-dimensional multipoint and multi-indicator warning method. The method comprises the steps that (1) risk level dividing is carried out on each indicator; (2) the numerical values of the indicators of the rainfall intensity, the rainfall pattern, the cumulative rainfall and the slope soil-rock body saturability of a certain landslide in a certain period of time are acquired; (3) according to the value of each indicator, an evaluation matrix is acquired; (4) according to the evaluation matrix, an entropy weight method is combined to determine the weight of the indicators of the rainfall intensity, the rainfall pattern, the cumulative rainfall and the slope soil-rock body saturability; (5) the multi-indicator comprehensive measure {A, B, C, D} of the landslide is calculated; (6) the confidence lambda 0.5 is introduced, and comparing is carried out to determine the risk level of the rainfall-type landslide; and (7) corresponding landslide warning is carried out according to the risk level of the rainfall-type landslide. According to the invention, the warning accuracy of the o rainfall-type landslide is greatly improved; the problems of the prior art are solved; warning standards are unified; and the warning method is suitable for popularization and application.

The invention provides a flame-retardant silicone adhesive and a preparation method thereof. The flame-retardant silicone adhesive is prepared from the following raw materials in parts by mass: 350 to600 parts of alpha, omega-dihydroxy polydimethylsiloxane, 100 to 200 parts of simethicone, 300 to 600 parts of flame retardant, 100 to 300 parts of inorganic filler, 5 to 40 parts of cross-linking agent, 2 to 20 parts of coupling agent and 0.5 to 2 parts of catalyst. The flame-retardant silicone adhesive provided by the invention is a dealcoholized flame-retardant silicone adhesive, is safer andmore environment-friendly than decarboxylated and deoximated flame-retardant silicone adhesives, and can have good mechanical properties and excellent flame-retardant effect by adding a specific flameretardant and alpha, omega-dihydroxy polydimethylsiloxane in an appropriate proportion.

The embodiment of the invention provides an intelligent agricultural machine operation management method and system, and the method comprises the steps of: obtaining a plurality of land parcel local images collected by an unmanned aerial vehicle, and the pose information of the unmanned aerial vehicle corresponding to the land parcel local images; splicing all the land parcel local images according to the corresponding unmanned aerial vehicle pose information to obtain a land parcel image; inputting the land parcel image and the key points of an operation area marked by a user into a trained semantic segmentation network model to obtain the operation area; and determining a path planning result according to the operation area, and sending the path planning result to the intelligent agricultural machine. According to the method, the land parcel image is obtained by splicing a plurality of land parcel local images collected by the unmanned aerial vehicle, manual collection by means of a high-precision GPS is not needed, collection by means of an agricultural machine provided with a high-precision GPS is also not needed, the farmland land parcel information obtaining mode is simplified, the data collection efficiency is high, and the precision requirement can be met. User experience and an artificial intelligence algorithm can be effectively combined, and the segmentation precision of the neural network is improved.

The invention discloses a design risk analysis method and system based on multi-system integration. The method comprises the following steps: obtaining experience information from experiment entrustment information, experiment report information, trial-manufacture problems, production problems and after-sales problems; establishing a product design failure mode and consequence analysis structure tree according to the bill of material data, and giving a product design failure mode and consequence analysis report by taking the product design failure mode and consequence analysis structure tree as a basis and referring to technical standard information and experience information; establishing a process design failure mode and consequence analysis structure tree according to the technological process list data, and giving a process design failure mode and consequence analysis report based on the process design failure mode and consequence analysis structure tree by referring to technological resource library data and experience information; and obtaining a product design risk analysis result according to the product design failure mode and consequence analysis report and the process design failure mode and consequence analysis report. According to the method, the risk analysis is more comprehensive, and the design and manufacturing misunderstanding is reduced.