189 results about "Study Object" patented technology

A system for simplified generation of systems for analysis of satellite images to geolocate one or more objects of interest. A plurality of training images labeled for a study object or objects with irrelevant features loaded into a preexisting feature identification subsystem causes automated generation of models for the study object. This model is used to parameterize pre-engineered machine learning elements that are running a preprogrammed machine learning protocol. Training images with the study are used to train object recognition filters. This filter is used to identify the study object in unanalyzed images. The system reports results in a requestor's preferred format.

The invention discloses a determination method for a partition D-STATCOM integrated optimization configuration scheme of a large-scale power grid. The method comprises the steps of first starting from a dynamic analysis method theory of a non-analytic complex power system, establishing a power system non-linear equivalent model, rapidly and accurately calculating system integration dynamic equivalence impedance and load static equivalence impedance of an a load node of a study area to obtain limit margin; enabling areas with total loads ranking at the top to be weak areas according to researched network load flow calculation analysis results, enabling dispatching partitions in the weak areas to be study objects, comparing voltage stability strength indexes of every partition to determine weak partitions so as to enable the weak partitions to serve as configuration study objects, utilizing the fact that an average value of substation impedance modulus margins of the partitions is a threshold value to determine reactive power compensation to-be-selected point sets, shrinking configuration point hunting zones, and comprehensively utilizing trace sensitivity index maximum points to determine configuration points; and finally utilizing an optimal model considering voltage dip risk cost to determine an optimal capacity.

The invention discloses an aero-engine body vibration characteristic analysis method. An engine body system is separated into a rotor system and a stator system, the rotor system and the stator are coupled through a fulcrum system and are simulated jointly through dynamic characteristics of the rotor system and the stator system; the engine body system is separated into the two study objects, i.e., a rotor bearing system and a stator bearing system, and then vibration response and dynamic bearing reaction of the rotor bearing system are simulated and analyzed through a finite element analysis platform under the action of unbalanced exciting force and rub-impact force to acquire excitory input of the stator system; at last, the acquired dynamic bearing reaction and the rub-impact force are loaded on the stator bearing system, and the vibration response characteristics of the stator bearing system is simulated and analyzed to acquire engine body vibration characteristics. The aero-engine body vibration characteristic analysis method has the advantages of reducing hidden fault danger in the design of aero-engines and providing decision bases and technical support for engine vibration faults.

The invention discloses a multifunctional study desk and chair, which comprises a study desk and a study chair, wherein the study desk comprises a desk table and a desk frame, the desk table comprises a desk top and a desk hopper, the desk top comprises a fixed panel and a movable panel, the fixed panel and the movable panel are connected, the movable panel is connected with the desk hopper through a damper and a lock buckle, the desk frame comprises two sets of lifting inner pipes and lifting outer pipes which are sheathed together, an easy-lifting regulator is arranged on the lifting outer pipes, one ends of the lifting outer pipes are welded on a desk foot steel pipe, the two ends of the desk foot steel pipe are provided with foot sleeves, the lower ends of the foot sleeves are provided with balance regulating screws, and the middles of the two lifting outer pipes are connected through a connecting rod. The height of the study desk and chair is adjustable, and the study requirement of students with different body heights can be met. The fixed desk top can be used for placing various study objects, and the movable panel can be regulated to form different angles according to different requirements. The multifunctional study desk and chair has the advantages that the functions are complete, the space utilization is sufficient, the sitting posture of children is specified, and the children also maintain a neatness-keeping study environment.

The invention discloses a fuzzy clustering image segmenting method with transfer learning function. The method adopts the classic fuzzy C fuzzy-means algorithm as the study object and is special for overcoming the shortcoming of the C fuzzy-means algorithm that the low capacity is provided for resisting the noise while facing the image with noise. During processing the new image, the image segmenting method is mainly carried out for the image with noise pollution. With the adoption of the fuzzy clustering image segmenting method disclosed by the invention, the reliable clustering information obtained by summarizing lots of past similar images under the C fuzzy-means algorithm can be effectively learnt and utilized, such information is always considered as the clustering centre; by introducing the reliable information into the current new image segmenting task, the current clustering task can be effectively guided, and the noise resisting effect can be achieved, therefore, more precise clustering centre and more precise image segmenting result can be obtained.

The invention discloses an SNP (single-nucleotide polymorphism) marker set for identifying pig breeds. The application method mainly comprises the following steps: by using 200 purebred Large White and Landrace individuals as study objects, carrying out genome SNP 60K chip scanning typing on all the samples of the two breeds; after carrying out quality control on all the data according to the requirements, screening out SNP marker sites capable of identifying Landrace and Large White, and carrying out genome correlation analysis to screen out 16 SNP sites for identifying Landrace and Large White; and carrying out verification on another 500 individuals by principal component analysis and cluster analysis, wherein the accuracy of the 16 SNP sites reaches 99%, which indicates that the 16 SNP sites can be used for identifying Large White and Landrace.

Provided is a flexible satellite attitude control method based on three-stage path planning, relating to the technical field of satellite attitude control. A flexible satellites with pyramidal CMG group as the actuator is selected as the study object, a satellite attitude control method combing the three-stage attitude path planning and rolling optimization tracking is proposed, a nonlinear state-space equation including satellite attitude dynamics, kinematics and flexible attachment vibration is established for the accurate prediction of satellite attitude future information. Based on the three-stage path planning strategy, the flexible satellite attitude maneuvering time is optimally designed, the vibration of the flexible attachments can be avoided when the satellite attitude maneuvering target is completed. By means of the nonlinear model prediction method, the attitude angular velocity curve and attitude angle position curve obtained by planning are taken as the desired tracking targets to design the rolling optimization tracking control law of the frame angular velocity of the pyramidal CMG group, therefore, the attitude wide angle rapid maneuvering control for suppressing the vibration of the flexible attachments can be realized.

The invention discloses an estuary wetland mangrove forest ecological rehabilitation afforestation method. The estuary wetland mangrove forest ecological rehabilitation afforestation method comprises the steps that a rehabilitation test area is divided into an upper stream, a middle stream and a lower stream; soil covered by regional advantage mangrove trees at different sea levels is selected as study objects, and the vacant field and a bare field serve as a reference; the response characteristics of different areas, different sea levels, the photosynthetic characteristics of different plants and chlorophyll fluorescence characteristics to an alternative flooding and high-salt environment, the response of dynamic growth of different mangrove forest vegetations to the alternative flooding and high-salt environment, the response of a plant-soil system to soil sedimentation, salt and alkalinity, the response of soil nutrients affected by the plants to the wetland environment, and the response characteristics of soil enzymes to the wetland environment are analyzed in sequence. The most comfortable living environment is sought for the estuary wetland mangrove forest plants according to the dynamic and static adaptation characteristics to the environment of different advantage mangrove forest plants in different areas. According to the estuary wetland mangrove forest ecological rehabilitation afforestation method, the plants adapting to the different wetland environments can be accurately selected, and the method can be used for ecological rehabilitation afforestation of an estuary wetland.

The invention provides a method capable of increasing the average recognition rate of emotion points. The method comprises the following steps of: making specifications of emotion data of an electroglottography and voice database; collecting the emotion data of the electroglottography and voice data; carrying out subjective evaluation on the collected data, and selecting one set of data subset as a study object; carrying out preprocessing on electroglottography signals and voice signals, and extracting short-time characteristics and corresponding statistical characteristics in the voice signals and MEL frequency cepstrum coefficient SMFCC; carrying out fast Fourier transform on the electroglottography signals and the voice signals, then dividing the electroglottography signals and the voice signals, and after dividing, obtaining MEL frequency cepstrum coefficient TMFCC; and respectively using different characteristic combination for carrying out experiment, and solving the average recognition rate of 28 emotion points under different characteristic combinations when a speaker is related and not related. The experimental result shows that by adoption of TMFCC characteristics, the average recognition rate of the emotion points can be increased.

The invention provides a method for predicting the key industrial electricity consumption based on an industrial condition index. The method comprises the following steps: (1) obtaining the key industrial condition index and historical electricity consumption data; (2) performing seasonal adjustment and a stationary test on the data; (3) judging whether the industrial condition index and the industrial electricity consumption have a causal relationship or not through a Granger causality test and determining an optimal lag period of the condition index; (4) creating a time sequence ARIMA (autoregressive integrated moving average) model of the key industrial electricity consumption, introducing the key industrial condition index into an original ARIMA model, and creating a regressive model; (5) on the basis of an AIC (Akaike information criterion), screening out an optimal model; (6) performing model popularization and application, and predicting the industrial electricity consumption in the future. The key industrial electricity consumption is taken as a study object, the electricity consumption and the influence of the industrial condition index on the electricity consumption are studied by introducing the industrial condition index, the key industrial electricity consumption is accurately predicted in combination with the time sequence model, and a basis is provided for development and planning of electricity industry in the future.

The invention discloses a method and system for deep integration and real-time compensation of micro-inertial measurement information. The method comprises the following steps: respectively acquiring angular velocity information, acceleration information and magnetic field intensity information of a study object; respectively carrying out real-time compensation on the angular velocity information, the acceleration information and the magnetic field intensity information by virtue of a deep learning method, so as to respectively obtain compensated angular velocity information, acceleration information and magnetic field intensity information; determining a first Euler angle according to the compensated angular velocity information, and determining a second Euler angle according to the compensated acceleration information and the compensated magnetic field intensity information; and determining an integration gain coefficient of a self-adaption gain method according to a mean square error of the first Euler angle and a mean square error of the second Euler angle, and integrating the first Euler angle with the second Euler angle according to the integration gain coefficient, so as to obtain the integrated Euler angle. According to the method and the system, the micro-inertial measurement precision can be increased, the stability and the reliability are high, the aging ratio is high, and the response speed is high.

The invention discloses a method for guaranteeing the smoothness of the machine tool output power by adjusting the machining code feeding speed. The method is designed mainly for the user demands and the technological characters of the aviation field, domestic high-grade numerical control machine tools serve as the study object, analogue simulation is carried out on the machining process through VERICUT software based on given complex structural member machining codes, secondary development is carried out on the VERICUT software, the machining codes are segmented, the feeding speed of the machining codes of various sections is pushed back according to the required cutting power value, the maximum feeding speed and the minimum feeding speed, speed statements of the feeding speeds at different sections are modified, and the smoothness of an output curve of the machine tool main shaft power is kept to the maximum extent. The method overcomes the defect that the VERICUT software cannot simulate the cutting force, the data relation among cutting parameters, the impact effect of limiting factors on the power and the optimal algorithm are found out, and the smoothness of the machine tool output power is guaranteed by adjusting the feeding speed so that safety of the machine tool, workpieces and tools in the cutting process can be guaranteed.

The invention provides a multi-data-stream anomaly detection method based on the context. The method comprises the following steps that 1, multiple data streams are obtained, and snapshots are generated; 2, the anomaly of the snapshots of the multiple data streams is quantified; 3, the anomaly of the data streams is quantified; 4, the anomaly of the data streams is recognized. The detection method aims to adopt the node anomaly detection of an isomorphism distributed computation system as the study background and adopt the data streams monitored by computational nodes as the study object, the anomaly detection method comprehensively considers the context information of the multiple data streams and the historical behavior information of a single data stream, and the detection rate is high.

The invention discloses a test device and method for research of a rock pore scale multi-phase flow motion characteristic. The device comprises a flow control system, a visual observation imaging system, a micro-model, and a data collection analysis system, wherein a microscopic model of a natural soil pore replica serves as a study object, the flow control system comprises three high-accuracy programmable microinjection pumps and pipelines, and can provide accurate, stable flow input, the visual observation imaging system mainly comprises a test workbench, an optical microscope system, an LEDlight source, a microfluidic pressure sensor, a rotary fixture, a CMOS high-speed camera, and an auxiliary support system, the data collection analysis system can automatically save image data of thewhole test process, pressures of the inlet and the outlet of the micro-model, and environmental pressure value of peripheral pressure in real time, and after the test is completed, post-processing ofimage data is completed through self-programming so as to perform analysis. The test process is simple to operate, results can be shown visually, and the results are highly reliable.

The invention discloses a CRISPR / Cas13a based food-borne pathogenic bacterium nucleic acid nano fluorescence trace detection method. The method includes taking food-borne pathogenic bacterium nucleicacid as a study object, and preparing food-borne pathogenic bacterium nucleic acid targets, food-borne pathogenic bacterium crRNA, and nuclease Cas13a protein purification and quenching fluorescent RNA reporting markers; utilizing nuclease Cas13a to perform accurate cutting on specific nucleic acid targets in trace pathogenic bacterium cells, and cutting the quenching fluorescent RNA reporting markers by utilizing the incidental cutting effects of the nuclease to release fluorescence that can be detected; and collecting fluorescence spectrum data with the help of a fluorescence spectrum system, obtaining the fluorescence intensity value of the maximum absorption peak of an up-conversion fluorescent nanomaterial, and constructing a quantitative determination model of up-conversion nano fluorescence intensity and food-borne pathogenic bacterium nucleic acid target content so that the rapid detection on food-borne pathogenic bacterium nucleic acid nano fluorescence trace can be realized.The method is short in detection period, strong in specificity and high in sensitivity.

The invention relates to a decision level text automatic classified fusion method, belongs to the field of data mining, and is applied to digital libraries, network content supervision, junk mail filtration and the like. The method takes information integration as a theoretical basis, takes a text automatic classification algorithm with high classification precision as a study object, and establishes a decision level text automatic classified fusion model, namely adopts a multi-layer fusion structure to perform text automatic classified processing in a serial-parallel hybrid mode so as to obtain classification results with higher precision.

The invention discloses a method for measuring the height of a tree and the volume of wood by means of a total station under the condition that the crown is covered. According to the method for measuring the height of the tree and the volume of wood by means of the total station under the condition that the crown is covered, the tree with the crowned covered serves as the study object, the total station serves as the measuring tool, the diameter d0 of the root portion of the trunk, the diameter d1.3 at breast height, 1.3m away from the ground, of the trunk, the trunk diameter dn of the highest position, within the vision reachable range, of the covered part of the crown, the distance h between the highest observable position and the ground, the trunk diameter dm of any position between the position, 1.3m away from the ground, of the trunk and the highest observable position, and the distance hm between the any position and the ground are measured in sequence, then the height of the tree and the volume of wood are measured and calculated accurately, field measurement processes are simplified, measurement intensity is relieved, and meanwhile the difficulty that the height of the tree and the volume of wood can not be measured under the condition that the crown is covered is overcome.

An intelligent auxiliary medical treatment decision supporting method of a two-stage mixed model mainly comprises the following steps that based on a subtractive clustering method, real medical treatment sample data information is subjected to weighting preprocessing, and a nonlinear indivisible feature space is converted into a divisible linear data feature space; based on an efficient extremity learning machine model, weighting feature data obtained by preprocessing are used, and a medical treatment decision supporting model is established by data self learning; and based on the established learning model, real medical treatment data are used, a study object is subjected to classification forecasting, and accordingly the fact that reliable efficient auxiliary forecasting support is provided for a target user is achieved. The intelligent auxiliary medical treatment decision supporting method has the main advantages that the method is simple and easy to realize, and forecasting results with high accuracy can be generated; the number of parameters involved in the method is small, parameter influence is low, namely needed human intervention is low, and operation is convenient; and the method is high in computing speed and efficiency.

The invention belongs to the technical field of control of fruit tree diseases and particularly discloses a method for screening citrus HLB (Huanglongbing) control agents through grafting. According to the method for screening the citrus HLB (Huanglongbing) control agents, a citrus scion infected with the disease is taken as an object, the content change of Candidatus liberibacter asiaticus in the scion infected with the disease and treated with the agents is detected quantitatively through a real-time PCR (polymerase chain reaction), and the control effects of the treating agents are evaluated on the basis. The citrus scion infected with the disease is taken as a study object directly, the agent efficacy evaluation more conforms to practical situations, and influence caused by an interhost such as Diaphorina citri Kuwayama or catharanthus roseus used in screening of Candidatus liberibacter asiaticus control agents is eliminated. The problems that a screening process of the Candidatus liberibacter asiaticus control agents is complicated, a reliable and effective evaluation system is absent and the like at present are solved, and reliable technical and theoretical bases are provided for control of citrus HLB.

The invention discloses an individual nutrients deficiency risk assessment method based on SNP (Single Nucleotide Polymorphism) site, which is named as INRAS (Individual nutrients deficiency risk assessment based on SNP). The method is aimed at N SNP site of an individual or N individuals of an SNP site as an experimental unit, the studied object is SNP site related to individual nutrient metabolism capacity, and primers are designed and synthesized according to locus information; DNA is then extracted out from the blood of the individual to carry out PCR (polymerase chain reaction) amplification, an assay result is then obtained by a fluorescence scanner, and finally, a risk assessment model is adopted to analyze the result. The risk assessment model disclosed by the invention, which is created on an evidence-based inclusion basis of SNP site, can accurately and systematically assess various nutrients deficiency risks of the human body on the basis of the SNP site; and a dynamic riskassessment model which is created on the basis of critical values of biochemical indexes of population nutrients can carry out accurate and systematic dynamic assessment on various nutrients deficiency risks of populations on the basis of the SNP site.

The invention discloses a blade machining process error prediction method based on extended error flow. The method is used for solving the technical problem that only geometric error sources are considered when multi-procedure rigid body part assembling or machining processes are adopted as the study object according to an existing error flow method. According to the technical scheme, the method comprises the steps that a model drive is adopted for conducting process monitoring, errors generated by a geometric positioning error source and errors generated by a force-carrying deformation error source are timely predicted, an error coupling and a transmission mechanism are studied, and a machining process error coupling modeling scheme is designed; infinitesimal division is conducted on a blade part through a grid division thought, and deformation analyses are converted to coordinate transformation of an infinitesimal coordinate system; a multi-source and multi-procedure error coupling model based on the extended error flow is built, and a composition error prediction model based on the error coupling model is given on this basis. According to the blade machining process error prediction method based on the extended error flow, working personnel can be helped to timely find manufacturing defects of the blade and correct and adjust the blade, reworking times are reduced and machining quality and efficiency are improved.

The invention provides a CMP (chemical mechanical polishing) simulation method, which comprises the following steps that any one interconnecting wire in an integrated circuit layout is selected as a study object; the study object is used as a reference, one planarization length respectively extends in at least four directions of the study object in the local plane of the integrated circuit layout, and dividing panes of the study object are formed; characteristic parameters of layout structures in the dividing panes of the study object are extracted, and the characteristic parameters at least comprise two of equivalent density, equivalent line width and equivalent gap; a CMP mold is adopted for carrying out CMP simulation according to the characteristic parameters; and metal dish-shaped and / or medium erosion simulation results of the study object are obtained. The simulation method has the advantages that the CMP simulation process is more accurate, and the physical and chemical mechanism of the CMP is better met, so the more precise chip surface topography after the CMP simulation can be obtained, and the qualified rate and the performance prediction accuracy of the chip are ensured.

The invention discloses a composite layer anti-interference control method for a deformable unmanned aerial vehicle. The method comprises the steps that an unmanned aerial vehicle with variable sweepand variable span. The method comprises the steps that the unmanned aerial vehicle with variable sweep and variable span is taken as a study object, and firstly, a nonlinear model of the unmanned aerial vehicle is subjected to Jacobian linearization; external gust interference and equivalent interference brought by parameter perturbation are considered, and a multi-cell LPV system model of the deformable unmanned aerial vehicle containing multiple interference kinds is built; then regarding a constant value and slow varying interference, an interference observer meeting the H8performance indexis designed for compensation, and an H8control law is designed for optimizing a closed loop transfer function regarding the conditions of not representing dynamic characteristics of the interferenceobserver and facing L2 bound norm bounded interference to inhibit bounded interference; finally, and the interference observer is combined with the H8control law to construct a composite layer anti-interference controller; the method has the advantages that the method of sorting and treating multiple interference kinds for the deformable unmanned aerial vehicle, and the method can be applied to interference control of composite layers of other motion bodies with more complex system models.

The invention relates to the technical field of composites, in particular to a rigidity predicting method for a 2.5-D woven composite. The 2.5-D woven composite is prepared from a yarn system and resin, wherein the yarn system comprises warp yarns and weft yarns. With one repeat unit cell formed by warp yarns, weft yarns and resin as a study object, a rectangle-hexagon mesoscopic geometric model is established, and an integral coordinate system is established based on the model; besides, the rigidity of the 2.5-D woven composite is measured with an ANSYS finite element software program. The error of a prediction value obtained through the rigidity predicting method for the 2.5-D woven composite and an experiment value obtained through a composite static tensile test is within 10%, and the purposes that the geometric structure of the composite can be truly reflected, and calculation can be simplified are achieved.

The invention provides a method for evaluating the reliability of a digital transformer substation relay protection system. According to the method, a model for analyzing the reliability of the digital transformer substation relay protection system is built by using information stream of a protection function as a study object and using the pattern modeling and reliability diagram analysis principle as the basis according to the composition and the characteristics of digital relay protection, and in addition, the example calculation is used as a concrete implementation mode. According to the reliability analysis method provided by the invention, the analysis and the calculation are carried out by using the known element reliability of elements for forming the relay protection system as the basis, the result can be used for evaluating the reliability of systems adopting different structures, so a more proper system composition mode is selected out, and the method can be used for early-stage planning of a digital transformer substation. A reliability modeling and calculation method provided by the method disclosed by the invention is more visual, the thinking is clear, and a reliability calculation model can be directly abstracted out directly through topological graphs of the digital transformer substation.

The invention belongs to the technical field of enzyme engineering, and relates to a method for improving the thermal stability of bacillus subtilis lipase A. According to the method, bacillus subtilis lipase A is taken as a study object, a crystal structure of bacillus subtilis lipase A is obtained from the RCSB (Research Collaboratory for Structural Bioinformatics) database firstly, and flexibility of different Loops of bacillus subtilis lipase A is analyzed by molecular dynamics; according to the rational analysis and combined with a proline effect theory, glycine residues which are located in the Loops with higher flexibility and obtained through screening are mutated to proline; a mutation result obtained through screening is verified through molecular dynamics simulation; and finally, hotspot residues with modified thermal stability are verified through a thermal stability experiment of a bacillus subtilis lipase A mutant strain.

The invention discloses a fast cauliflower genetic purity detection method based on the polymerase chain reaction (PCR) technology. The method uses cauliflower hybrids of 100-day oriental snow as study objects, the screening of molecular markers is carried out, and seedling blade genome deoxyribose nucleic acid (DNA) and special primer combinations SREM8-1 / SRodd58 capable of simultaneously generating male parent and female parent special strip markers in the hybrids can be verified. Through the adoption of the primer, the method has the advantages that the accuracy is high, the results are stable, the influence caused by environment conditions and development period is avoided, the counting is simple and convenient, and the like, the seed genetic purity of the cauliflower hybrids of 100-day oriental snow can be simply, fast and accurately detected, the efficient and accurate quality control of cauliflower seeds is favorably realized, and the quality detection process of the cauliflower seeds is accelerated.

The invention relates to a pulsatile delivery sustained-release tablet for treating diabetes mellitus and a preparation method thereof. The active components of the pulsatile delivery sustained-release tablet liraglutide, exenatide acetate or pramlintide acetate are respectively combined with insulin, and drugs are released according to a preset time. According to the pulsatile delivery sustained-release tablet, a polymer material is adopted as a coating film, the active components are combined with a swelling coating to serve as a tablet core, and medical auxiliaries are adopted. The dissolution percentage of the composition is further investigated, and an SD (sprague-dawley) diabetes rat model is used as a studying object to detect the fasting blood-glucose, 2hplasmaglucose, number of hypoglycemia times, dawn phenomenon indexes of the rat model, and the treatment effects are investigated.

The invention relates to a lead-free solder for hot dipping of a solar battery and a preparation method thereof. The lead-free solder contains a Sn-Bi-Sb lead-free solder with the purity of 99.99% and the Sn: Bi: Sb mass ratio of (98.9 to 93.5): (1 to 4): (0.1 to 2.5), wherein In 0 to 3 wt%, Ag 0 to 0.5 wt%, Zn 0 to 2 wt%, Cu 0 to 2 wt%, Al 0 to 1 wt%, rear earth elements 0 to 1 wt%, and P 0 to 1 wt% are added into the Sn-Bi-Sb lead-free solder. Using Sb used as the substitute of Ag can greatly reduce the cost of the solder alloy, keep the advantages of the conventional Sn-Pb solder, improve the utilization rate of the solder, save the material, and improve the weldability. The surface quality is improved by plating tin on a copper sheet so as to improve the production level and the product quality of a solar battery to a new level. The high-performance solder alloy has a good development prospect when being taken as a studying object to strive for meeting the industrial application requirement.