83results about How to "Reasonable guidance" patented technology

The invention provides a searching and sorting method and device based on a click rate. The problems that when a sorting rule is used for sorting searching results, the reusability is low and the method is cumbersome are solved. The method comprises the steps that before searching and sorting, the click data of a user within preset time are acquired, and the weight of each feature is determined according to the click data; the searching and sorting comprise the following steps that search terms and search targets matched with the search terms are acquired, and the features of the search terms and the features of the search targets are extracted respectively; for all search targets, the click rate of the search targets is forecasted by using a regression model according to the features of the search terms, the features of the search targets and the corresponding weights of the features; according to the click rate, the search targets are sorted and displayed to the users. The searching and sorting method and device based on the click rate are suitable for various application scenarios, and high in reusability. Moreover, the weights can be adjusted accurately in real time according to the click data of the user, and reconfiguration is of no need.

The invention relates to an application method of a three-dimensional scanning technology in building engineering based on a BIM. The method comprises the steps of scanning a construction site and surroundings through the three-dimensional scanning technology, and generating data; establishing a BIM three-dimensional model of the construction site and the surroundings; guiding site construction through the BIM three-dimensional model of the construction site and the surroundings; establishing a BIM three-dimensional model of design paper; establishing a BIM three-dimensional model of a finished process; comparing the BIM three-dimensional model of the design paper with the CAD model of the paper of a designing institute or the BIM three-dimensional model of the design paper; and modifying or perfecting the finished process if there are deficiencies or defects.

The invention belongs to the field of social network analysis, and discloses an information situation awareness and propagation management and control model based on node influence. The model comprises a data acquisition module, a characteristic extraction module and an information situation awareness and propagation module, wherein the data acquisition module obtains source data from a social network, obtains the personal attribute, the historical behavior and the friend relationship of a node from the source data, and constructs an information propagation network; the characteristic extraction module independently extracts characteristics from two dimensions including a network dynamic attribute and an interaction dynamic attribute, and independently calculates corresponding factor functions; and the information situation awareness and propagation module constructs the information situation awareness and propagation management and control model on the basis of a mean-field theory, simulates an information propagation tendency, perceives an information diffusion tendency, captures the peak hour of information outburst, and mines a dynamic factor which drives the information to be propagated. By use of the method, the dynamics reason of the information propagation in an on-line social network can be effectively explained, an information propagation evolution situation in the social network is perceived, and the method can be widely applied to the relevant field of information propagation.

The invention relates to a deep learning stock market prediction method combined with financial news, and the method comprises the following steps: S1, a web crawler technology is utilized for financial news to crawl relevant financial information corresponding to a stock from Sina financial news and Netease financial news and save the information to a local database, and a financial news document database is formed; S2, the financial news information is processed, and news emotion analysis is performed; S3, an RNN deep learning network based on LSTM is provided; S4, training characteristics are extracted; and S5, model training and prediction are performed. According to the invention, a technology of news emotion analysis is utilized, the RNN deep learning network based on LSTM is adopted, the most common technical indexes used by financial market investors are combined with the method to perform feature vector prediction, and good effect is achieved.

The invention discloses a county-level road accident forecasting method based on geographic weighting Poisson regression. Firstly history road accident frequency data of each county in a research scope are collected through data survey; then a model relation between county-level accident frequencies and influencing factors and a geographic position matrix form of influence coefficients of each variable quantity are set, and a geographic weighting function in a parameter estimation process is carried out; and parameter estimation is carried out on a Poisson regression model according to geographic weighting. A problem that existing county-level road accident forecasting does not give consideration to spatial heterogeneity to cause not-high forecasting accuracy is solved, and scientific and reasonable guidance is provided for county-level road accident forecasting and safety prevention and control policy formulating.

The present invention relates to Gibberella zeae (asexual state Fusarium graminearum) detection and a tube detection method of using the detection to confirm medium level of drug resistance produced by carbendazim, which is special for the specificity detection of Gibberella zeae strain and medium level of drug resistance produced by carbendazim. The method adopts the ASO-PCR detection to the pathogenic germs on the diseased spike, diseased tissue and diseased body collected from field, the entire process only requires 6h, and the detection accuracy rate is 99%. The method has fast, simple, accurate and sensitive features.

The invention relates to a smart city emergency rescue channel system and method. The system comprises a background center scheduling system, an intelligent road infrastructure unit, a warning indicator, a rescue planning request terminal and a V2X emergency rescue channel sensing terminal. A smart city emergency rescue channel system is constructed through the V2X technology and an emergency rescue channel is planned in real time, so that emergency accident rescue is rapidly and effectively guided and assisted. The smart city emergency rescue channel system and method are characterized by seamless access to the smart city ecology to adapt to the future city planning and science and technology development.

The invention discloses an automatic addressing method for newly establishing a railway station in a mountainous area. The method includes the steps that first, a station address searching parameter is determined and track sections are divided; second, each track section is divided into a plurality of grids, and geographic information data are acquired and serve as grid attributes; third, the grids where the station cannot be established are rejected; fourth, whether one section needs to be provided with the station or not is judged, if not, the next section is judged, and if yes, the fifth step is performed; fifth, the station addressing range is determined; sixth, the evaluation indexes affecting station establishment are selected, the weights of all the evaluation indexes are determined according to an analytic hierarchy process, the evaluation values, corresponding to the evaluation indexes, of the grids are calculated, and the station establishment suitability degree values of the grids are obtained; seventh, an optimal station address is selected and a station site direction is determined; eighth, whether the next section needs to be provided with the station or not is figured out, if yes, the fifth step is executed till the optimal station addresses of the whole track are searched for. Through the method, the station addresses meeting various constraint conditions of addressing of the station can be automatically searched for, and the automation degree is high.

A Fusarium graminearum beta 2-microtubulin gene for detecting the resistance of Fusarium graminearum to carbendazim and its ASo-RCR detection method are disclosed. The whole length of said gene contains 997 nucleotides, one intron and the drug-resistant mutation site. It has high detecting speed (4 hr) and correctness (99%).

The invention discloses a station-level photovoltaic tilt angle optimizing method considering economic factors. The method includes the following steps of firstly, determining basic information parameters of a photovoltaic power station; secondly, clearly determining the establishment scale of the photovoltaic power station, and establishing a photovoltaic power station productivity model; thirdly, establishing an economic model of the photovoltaic power station; fourthly, calculating the unit cost electrovalence LCOE on the basis of the photovoltaic power station productivity model in the second step and the economic model in the third step; fifthly, obtaining an optimizing model of the photovoltaic power station by means of a genetic algorithm with the minimum unit cost electrovalence as the optimizing target to obtain the tilt angle, namely the optimal tilt angle, of a photovoltaic array at the minimum unit cost electrovalence. By means of the method, a photovoltaic panel is free of shadow shield in most of sunshine period everyday all year round, and the economic benefits brought by a photovoltaic power generation system are improved.

The invention discloses an active moving method of a moving sink node in a wireless sensor network, and belongs to the technical field of the wireless sensor network. According to the method, on the basis of a tree form route multi-hop interconnection model of the wireless sensor network, one-hop neighbor nodes of a current sink node are taken as subtree roots, subtrees are divided to form subtree sets, and the maximum value and the minimum value of remaining energy of a sensor node in each data propagation path in each subtree within a certain range are obtained through the sink node; then according to certain conditions, a dying node sequence and a sink feasible moving position sequence are generated; the sink node selects a proper position in the sequences to move. The sequences are stored in the sink node for a long time and are updated according to energy of a node of the next round. Accordingly, the sink node can be guided to move by mastering extreme values of network energy within a certain range in real time, energy balance among network nodes can be achieved gradually, and time and energy cost brought by a large quantity of repeated inquiries can be effectively reduced at the same time.

The invention belongs to the technical field of monitoring of crop diseases and in particular relates to a method for determining wheat head scab levels based on a cloud model. The method comprises the following steps: extracting disease areas, constructing color characteristics, generating a gibberella saubinetii color characteristic cloud model, establishing a comprehensive evaluation model andanalyzing the evaluation model. By utilizing the relationship between color changes in the disease areas and wheat diseased panicle rate levels in the gradual pathologic process of wheat head scab, the color characteristic cloud of the disease areas is obtained by combining with three numerical characteristics of the cloud model, the wheat head scab levels are subjected to non-rigid diversion by utilizing the cloud model, and comprehensive evaluation is realized.

The invention discloses a bicycle-mode traveling selection forecasting method based on an activity chain mode. The forecasting method includes the steps that the data survey is carried on a situation of resident traveling, and the survey result is managed and added up; a selecting mode of the resident traveling in a day in the data survey result is extracted, and the traveling mode is carried out on a variable virtual operation and a coding operation; a correlated variable in the activity chain mode is input to multi-term logit models, and a coevolution logit model can be obtained through calculating; the calculated coevolution logit model is carried out on iterative operation, and two selecting results of traveling modes are recorded; the two selecting results of the traveling modes are carried out on statistics and analysis, the prediction accuracy is carried out on contrastive analysis. By the statistics and the analysis of the vehicle selection of residents in urban, the proportion of the bicycle-mode traveling selection can be accurate to forecast, so that the urban traffic planning and the decision of the policy can be provided with the scientific and reasonable guidance.

The invention discloses a method for detecting density of passengers in a bus on the basis of image analysis. The method includes the steps that (1) a binocular camera is arranged at the front end of the inside of the bus, and video images are shoot; when no passengers are in the bus, the images of the binocular camera are processed, so that depth images of the background in the bus are obtained; (2) a foreground objective of the area where the passengers stand in the bus is obtained; (3) by means of the perspective effect of the binocular camera, perspective correction is carried out on the image of the foreground objective of the area, the density is primarily divided into a low level and a medium and high level according to the area of the foreground, and if the density is in the medium and high level, the fourth step is carried out; (4) the video image of one camera body of the binocular camera at the same moment is captured and grayed, and texture features of the image are extracted; (5) detected passenger density information and geographical position information are stored. The method effectively solves problems occurring in the prior art, and the density of the passengers in the bus is detected by analyzing the images shot by the binocular camera.

The invention discloses a method for optimizing the installation inclination angle of a photovoltaic panel based on representative horizontal plane radiation data, which can be applied to scientific researches and engineering applications in the fields related to renewable energy sources. In the invention, a method for determining the monthly optimum inclination angle, the season optimum inclination angle and the annual optimum inclination angle of a regional photovoltaic panel is put forward by using a solar radiation monthly mean model on an inclined plane based on representative daily solartotal radiation monthly mean value data on a horizontal plane, and the optimum inclination angle in different time periods is comprehensively analyzed. The method disclosed by the invention is applicable to various geographical and climatic conditions and has important significance in research for technologies related to photovoltaic power generation planning.

The invention discloses a medical monitoring and interactive system. The system comprises a medical monitoring end, a cloud server and a medical institution end, wherein the medical monitoring end comprises a monitoring module and a user end; the monitoring module comprises a monitoring device and a processing module; the monitoring device is used for monitoring a vital sign signal; the processing module is used for receiving the vital sign signal collected by the monitoring device and processing the vital sign signal into vital sign parameters; the user end comprises a storage module used for displaying and storing the vital sign parameters transmitted by the monitoring end and uploading the vital sign parameters to the cloud server; the medical institution end comprises an information monitoring module and a pushing module; the information monitoring module is used for monitoring the user vital sign parameters transmitted by the cloud server; the pushing module is used for pushing information to the cloud server; and the information includes at least one of user vital sign parameter interpreting information, alarm reminding information, monitoring reminding information and health guidance information.

The invention discloses a land use combination form determination method related to road traffic accident risks. The land use combination form determination method comprises steps of collecting history data and other parameters of each traffic analysis district in a research range, performing dividing on a land use combination form through a clustering method, establishing a geographic weighted regression model according to a partitioning result and extracting a risk land use form highly correlated to traffic accidents, constructing a determination analysis function, establishing determination methods for various land use combination forms, performing determination on a land use combination form of a newly-provided traffic analysis district on the basis of a determination analysis function, and determining risk land use characteristics. The land use combination form determination method related to road traffic accident risks overcome a past problem of lack of variety of land use characteristic representations and spatial heterogeneity, can accurately improve result accuracy and can provide a scientific and reasonable guidance to land planning and traffic safety prevention and control policy.

The invention provides an airport terminal passenger splitting guide system with a face information collection function. The airport terminal passenger splitting guide system comprises a device consisting of five parts, namely a passenger face image collection apparatus, a personnel blocking device, a passenger identity identification apparatus, a computer provided with a passenger flight data system, and a splitting guide display, and an airport flight departure system and a flight inquiry system, which communicate with each other through the computer. The airport terminal passenger splittingguide system provided by the invention blocks passengers with preset conditions and guides security inspection ports where the passenger needs to go, thereby realizing orderly splitting and reasonably dredging the passengers, and the airport terminal passenger splitting guide system has the significant advantages of being convenient, timely, accurate and time-saving.

The invention belongs to a molecule detection method of Fusarium graminearum to medium resistance level bacterial strain of carbendazim. The method can be used for monitoring drug resistance of Fusarium graminearum to carbendazim and prevalence warning, wherein Fusarium graminearum can cause wheat scab. The detection method includes the following three main steps: (1) nuclear genome DNA of bacterial strain to be detected is respectively extracted: (2) internal and external primer pairs are utilized to carry out nested PCR, thus obtaining a target segment; (3) the target segment is respectively restricted by restriction enzymes HindIII and TaaI (Tsp4CI), and genotype of medium resistance level bacterial strain can be accurately identified by virtue of a restriction product electrophoresis spectrum. By adopting PIRA-PCR (primer-introduced restriction analysis PCR) technology, quantity of Fusarium graminearum with medium drug resistance in field and ratio thereof in group can be rapidly and accurately detected. Detection accuracy reaches more than 95%.

The present invention belongs to the field of one kind of nanometer decalcified bone matrix (DBM) material with weak antigenicity and good osteogenesis inducing activity for bone regeneration and its preparation process. The preparation process includes the following steps: 1. obtaining fresh health adult bone, eliminating soft tissue, obtaining bone blocks of different sizes, flushing in flowing water for 2-6 hr, dewatering with anhydrous alcohol for 1-3 hr, defatting with ethyl ether for 0.5-2 hr, air drying, freeze drying at -10 to -100 deg.c in a refrigerator and grinding in a mill into 0.5-2.5 mm size grains; 2. soaking in anhydrous alcohol for 1-3 hr soaking in ethyl ether for 1-3 hr, rinsing with distilled water for 2-5 times, soaking in hydrochloric acid for 2-8 hr, soaking in ethyl ether for 0.5-2 hr, air drying to obtain DBM and freeze drying at -10 to -100 deg.c in a refrigerator; and 3. grinding DBM in a grinder to 1-300 nanometers and gamma ray or ethylene oxide sterilizing.

The invention discloses a road condition broadcasting method and system based on cloud short-term path prediction. The method comprises the following steps: a vehicle-mounted terminal acquires vehicleposition coordinates, and the coordinates are sent to a cloud server through wireless communication; the vehicle-mounted terminal converts the vehicle position coordinates, the cloud server calculates the driving distance of the vehicle according to the position data received in real time, and the received vehicle position is saved to a database; based on an RNN trained by successive data of thedatabase and the current travel data, the cloud server predicts the driving path of the vehicle; the road condition information of road sections within a radius coverage area and the road intersectiongenerated by the predicted vehicle travel paths are taken, and the congestion road section information which needs to be broadcasted can be acquired; and through a TTS technology, the vehicle-mountedterminal converts formed text information to voice to be broadcasted. Delays caused by accidents or road congestion and the like can be reduced, a vehicle flow can be reasonably and effectively evacuated, the time on the road is saved, and safety hazards are reduced.

The invention discloses a personality characteristic prediction method and system based on network behaviors. The method comprises the steps of obtaining user behavior data; marking personality characteristics of users; performing data preprocessing and feature extraction on the acquired data; performing data integration on the data features extracted in the set time period according to the occurrence time sequence to form behavior vector features containing a time sequence relation; and making the behavior vector characteristics of the users correspond to the marked personality characteristics, inputting the corresponding data into a long-short-term memory model for prediction, and outputting a prediction result of the personality characteristics. The method has the advantages that personality characteristics of users can be automatically predicted; heterogeneous data of a social platform are used, and automatic calculation and prediction of the personality of the users are achieved.

The invention belongs to high-throughput molecular detection of Fusarium graminearum on carbendazim medicament-resistant gene frequency, which can be used for monitoring the medicament resistance of the Fusarium graminearum and early warning medicament-resistant epiphytotic disease of the Fusarium graminearum. The invention provides medicament-resistant high-throughput detection technology constructed based on the fact that over 97 percent of Fusarium graminearum medicament-resistant genetype to carbendazim results from mutation of the 167th locus of beta2-microtubulin gene. The detection method mainly comprises the following three steps of: (1) respectively extracting known sensitive and medicament-resistant strains and genome DNA of samples to be detected; (2) performing specific real-time quantitative PCR reaction and establishing a standard curve; and (3) contrasting the standard curve to solve the medicament-resistant gene frequency in the detected samples. The method has the characteristics of high throughput, rapidness and accuracy. The sensitivity of detecting the medicament-resistant gene frequency is millionth to one hundred thousandth, and the accuracy rate is over 96 percent.

The invention discloses a concrete structure of an environment-friendly pharmaceutical waste gas treating device. In the technical scheme, an upper suspension assembly, a middle bearing assembly, a lower supporting assembly and a spinning assembly are additionally arranged inside the device body creatively, the advancing route of waste gas to be treated can be guided reasonably in the pharmaceutical waste gas treatment process through the cooperation of the related assemblies, and at the same time, the treating effect of a spraying device can be improved efficiently.

The present invention belongs to a real-time detection method of the frequency of drug resistance genes in Sclerotinia sclerotiorum syngen, which can be used for drug resistance monitoring and popularity warning of carbendazim and other benzimidazole fungicide resistance in sclerotinia sclerotium disease of cole and the like crops. The detection method is divided into three major steps, the first step: respectively extracting the nuclear genome DNA of known drug-resistant strains, sensitive strains and sample to be measured; the second step: using the specific detection primers of drug-resistant strains and Sclerotinia sclerotiorum strains for real-time quantitative PCR reactions, respectively establishing the standard curves of the drug-resistant strains and Sclerotinia sclerotiorum strains detection; the third step: sample to be measured respectively using the two specific primers for real-time quantitative PCR reactions, contradistinguishing with the established standard curves, obtaining the corresponding numbers of the drug-resistant strains and sensitive strains and the proportion of the drug-resistant strains in the total number of the Sclerotinia sclerotiorum. The use of real-time quantitative PCR technology can perform high-throughput, rapid and accurate quantitative detection of the number of field drug-resistant Sclerotinia sclerotiorum and its proportion in the pathogen syngens, which has high-throughput characteristic. Compared with the conventional biometrics and general PCR detection of drug-resistant strains, the invention is time-saving, cost-saving and fast. The whole process from directly extracting the genome DNA from the sclerotia, disease spots and spores collected to real-time quantitative-PCR detection is only 6h needed, and the detection accuracy rate is more than 96%.

The invention discloses a traffic navigation method and device for variable destinations and belongs to the technical field of intelligent traffic services. The method comprises steps of obtaining a regret level of a user; determining a destination primary selection set through the POI classification code information; sorting the destination primary selection set according to the regret level, andrecommending a destination to a user; searching a path by taking the minimum regret impedance of a destination-path as a decision criterion, and determining the navigation path information. The method is advantaged in that the method can reasonably guide the user to change decision, effectively improve travel efficiency in the prior art, alleviate the traffic jam, avoid waste of commercial resources, and solve a problem that an idea that the destination of the travel of the user is changed due to road jam and the like is not reasonably induced.

The embodiment of the invention discloses a method and a device for controlling a vehicle. A specific embodiment of the method comprises the steps of obtaining first point cloud data collected by a vehicle in a driving process; identifying an obstacle in the first point cloud data; determining second point cloud data according to the first point cloud data and the identified point cloud data corresponding to the obstacle; clustering the second point cloud data, and determining at least one obstacle corresponding to the second point cloud data according to a clustering result; and according to the determined at least one obstacle, sending a control signal to the vehicle to control the vehicle. According to the method, the point cloud data corresponding to the unknown type of obstacle can be further processed so as to guide the vehicle to run more reasonably.

The invention provides a DTP pharmacy management method. The method includes the following steps of: information acquisition: patient information is acquired; medicine treatment management: medicine treatment information is acquired and managed according to the patient information; and fee management: and fee payment information is acquired according to the patient information. Accordingly, the present invention also provides a readable storage medium and a DTP pharmacy management system. With the DTP pharmacy management method, the DTP pharmacy management system and the readable storage medium of the invention adopted, high-value medicine sale and distribution are provided for patients, and the comprehensive management of various professional pharmaceutical services including follow-up medicine aid, patient education and medication consultation can be realized.

The invention belongs to the field of molecular biological detection. Specifically, the invention belongs to the field of detection of pathogens causing respiratory tract infection; and more specifically, the present invention can simultaneously detect influenza A virus, influenza B virus, rhinovirus, respiratory adenovirus, respiratory syncytial virus, and mycoplasma pneumoniae. By using a composition provided by the invention, the six pathogens causing respiratory tract infection can be detected at the same time, and specific infection of one or more pathogens can be identified. Meanwhile, the detection rate is higher than that of the existing composition, and the detection is more accurate.