36results about How to "Simple steps to follow" patented technology

The invention provides a method and an apparatus for generating an index for a table in a database. The method for generating the index for the table in the database comprises the steps of in response to the reception of a query statement for performing query for the table, searching for one or more rows meeting a query condition in the query statement in the table; based on identifiers of one or more rows, establishing a result list; and generating the index used for the query statement, wherein the index comprises information associated with the query condition and the result list. The invention further provides a method for performing operation in the table of the database based on the index. The method comprises the steps of analyzing the query condition and the result list from the index; in response to the reception of a second statement for performing operation for the table, determining at least one part, matched with a second condition in the second statement, of the query condition; and based on one or more rows indicated by the identifiers in the result list in the table, executing the second statement.

The invention discloses a remote sensing estimation method for the thickness of sea ice. The remote sensing estimation method comprises the steps that a ground echo waveform is obtained from a CryoSat-2 radar altimeter, a raw echo waveform is fit through a composite cubic Bezier curve, the position of a waveform re-tracking point is solved, the freeboard height of the sea ice is calculated, and meanwhile, data such as the accumulated snow depth and the sea ice type in the same period are obtained; the data are subjected to geographical coordinate matching to obtain point data containing the freeboard height of the sea ice, the accumulated snow depth and the sea ice type; different sea ice densities are given to one-year ice and multiyear ice, by combining the accumulated snow density withthe seawater density, the thickness of the sea ice is estimated through a hydrostatic model, and finally a sea ice thickness distribution diagram in a study area is obtained through projection transformation, raster conversion and space resampling. According to the remote sensing estimation method, a novel waveform re-tracking method, namely a composite cubic Bezier curve fitting method, is adopted, the problem that an original method is sensitive to the surface characteristics of ground features is solved, and thus the estimation accuracy of the thickness of the sea ice is improved.

The invention relates to a planeness error evaluation method and device. The method includes initiating a rotary angle and a current optimal planeness error; projecting a to-be-tested dot set of a component plane to a projection face under the rotary angle; determining a two-dimensional boss of a projection point in the projection face; determining the minimum dot line distance in the two-dimensional boss; judging whether a minimum area condition is met or not; updating the current optimal planeness error; judging whether a convergence condition is met or not for determining a final planeness error evaluation result. The method provided by the invention is small in calculation amount. The two-dimensional boss of the projection dot set on the projection face is generated by adopting a boss quick generation method and easy implementation is achieved. At the same time, by changing the rotary angle of the projection face, different two-dimensional bosses can be obtained and a solution meeting the minimum area condition can be found. The execution steps are simple and are easy to realize through programming. Therefore, the method and device provided by the invention is easy to apply in practical engineering.

The invention relates to a glacieridentification method based on acorrelation coefficient threshold. The method comprises steps as follows: firstly, an SAR (synthetic aperture radar) image is processed by original data reading, image registration, interferogram calculation, coherence estimation, flat ground phase removal, phase filtering and geocoding, correlation coefficientmaps are obtained, anda glacier area has a low-coherence characteristic on the correlation coefficient maps; a curvilinear relationship between coherence coefficient values and corresponding pixel number in the correlation coefficient maps in a research area is fitted, a first-order derivative of the curvilinear relationship is solved, a place where the first-order derivative curve becomes flat is taken as a transition point from the glacier area to a non-glacier area on the image, and a selected threshold b is obtained; the correlation coefficient maps are classified with a rule-based object-orientedclassification method, and the classification rule is set as follows: gamma is smaller than b; finally, the obtained image is subjected to post-classification processing including small pattern spot removal, raster-to-vector conversion, removal of abnormal holes in a planar object and serrated edge smoothing, and the glacier zone boundary is obtained.

The invention relates to an estimation method for the volume change of a subglacial lake. The estimation method comprises the steps that L1B waveform data in an SARIn mode of a CryoSat-2 radar altimeter in the corresponding time period are obtained; the surface elevation of a subglacial lake area is calculated through a waveform re-tracking method; obtained surface elevation data are pretreated toremove elevation change anomaly points; the pretreated elevation data are subjected to slope correction through a DEM to remove the error caused by the slope; 100*100 m of grids are finally generatedthrough kriging interpolation, then the elevation change in the corresponding time period is calculated, back scattering energy is added into elevation change values for correction, and the influenceof the back scattering energy to the elevation change is eliminated; and the shape and area of the subglacial lake are obtained through the elevation change values, the elevation change values of thesurface of the subglacial lake of each grid are integrated, and finally the volume change of the subglacial lake in the corresponding time period is obtained. According to the estimation method, fluctuation of the surface of the subglacial lake can be accurately and effectively reflected, and thus the volume change of the subglacial lake is estimated.

The invention relates to an SAR (Synthetic Aperture Radar) image glacier recognition method based on texture feature assistance, which is used for recognizing a glacier by utilizing an interference measurement method of Sentinel-1A data and combining texture information. The method comprises the following steps: utilizing Sentinel-1A data to carry out interference processing to obtain a coherencecoefficient graph; extracting seven textural features of mean value, variance, homogeneity, contrast, dissimilarity, entropy and correlation of the coherence coefficient graph; and comparing glacier extraction effects among different texture feature combinations. And selecting four textural features of mean value, variance, homogeneity and dissimilarity under the VV polarization mode with the highest classification precision, and training by utilizing an SVM classifier to obtain classes of glaciers, rocks, accumulated snow and the like. And converting the classified data into a shape format, and segmenting the data through ridge lines to obtain a glacier boundary data set. Compared with a traditional threshold segmentation method based on a coherence coefficient graph, texture features areintroduced, and glacier recognition is more accurate.

The invention relates to a sea ice thickness estimation method based on experimental data of a multi-beam altimeter (MABEL). The method comprises the following steps: preprocessing MABEL data, extracting altitude and coordinate information for matching, and removing an atmospheric effect; then performing time shaft equal division and altitude division, constructing a two-dimensional grid, and extracting an interval with the largest number of photons; performing treatment of calculating mean variance and the like to further eliminate invalid photons to acquire a sea surface contour line; and finally, estimating the sea ice thickness by combining a hydrostatics equilibrium formula according to the sea ice height out of water. Compared with the traditional method, the MABEL data is introduced into the method provided by the invention to estimate the sea ice thickness, so that the precision is higher.

The invention discloses a system and a method for finding, storing and fetching an article intelligently for a terminal; the system comprises a sending module and a receiving module, wherein the sending module is used for sending a storing-fetching instruction of the article, and sending a storing-fetching finished instruction when finishing storing and fetching the article; and the receiving module is used for generating first response message when receiving the storing-fetching instruction, and generating second response information when receiving the storing-fetching finished instruction. According to the technology disclosed by the invention, an intelligent terminal and an article storage area are associated via a wireless communication method such as ZigBee technology and the like, so the time that a staff stores and fetches the article is greatly reduced, the working efficiency is improved, and the intelligence of finding, storing and fetching the article is realized.

The invention discloses a sea ice type remote sensing classification method based on a convolution neural network, and belongs to the field of remote sensing geoscience application technology. The method uses satellite radar altimeter data to classify sea ice (divided into multi-year ice, one-year ice and open water). The steps include obtaining longitude and latitude coordinates of measurement points from altimeter data and radar echo waveform; downloading the sea ice type data and extracting the sea ice type information at the corresponding measurement point. The extracted data information is spatially matched and converted into vector point data with longitude and latitude coordinates. The radar echo waveform and the corresponding sea ice type are used as training data to train the convolution neural network, and the radar echo waveform to be classified is used to identify the sea ice type. After classification, the sea ice types are marked on the vector data. The tagged vector dataare processed by projection transformation, raster transformation and spatial resampling to obtain the sea ice type of the whole study area.

The invention belongs to the field of aircraft trajectory analysis application, and particularly relates to a civil aircraft flight stage identification method based on airborne data, which comprisesthe following steps: preprocessing a flight path; dividing a vertical motion situation according to the preprocessed flight path; correcting the divided vertical motion situation; dividing flight stages according to the vertical motion situation; constructing a flight state characteristic model according to the characteristics of the flight stage; and dividing the flight stages according to the preprocessed flight path and the corrected vertical motion situation. Re-identification and re-division of the flight stages are achieved, aircraft models do not need to be distinguished in the implementation process, the execution steps are relatively simple and easy to implement, the problem of flight stage division errors in QAR data can be solved, Technical support is provided for flight stage feature analysis of civil aircrafts.

The invention discloses a paging display method and apparatus, user equipment and a storage medium. The method comprises the steps of obtaining to-be-paged data in response to a paging display instruction input by a user; performing initial sorting on the to-be-paged data through a preset windowing function, and adding corresponding initial sorting sequence numbers to data entries in the to-be-paged data in the initial sorting process; and reading the initial sorting sequence numbers, and performing paging display on the data entries in the to-be-paged data according to the read initial sorting sequence numbers. Differing from existing ''three-layer nested query'' in which the data is sorted and traversed and the corresponding sequence numbers are added for the sorted data, the two-step operations of data sorting and sequence number adding are finished in one step through the preset windowing function, and the ''three-layer nested query'' is simplified into ''two-layer query'', so thatthe overall query speed is remarkably increased and the technical problem of relatively low query speed of existing paging display operation is solved.

The invention relates to a remote sensing estimation method for the black carbon concentration in accumulated snow. The method performs regional scale black carbon concentration estimation based on the combination of MODIS daily accumulated snow synthetic products (MOD10A1 and MYD10A1) with a 500 meter spatial resolution and actually-measured black carbon concentration data of ground stations. The method comprises the steps of performing image fusion, map projection conversion and data format conversion on the MODIS daily accumulated snow products to acquire research area accumulated snow albedo data; performing cloud-removing synthesizing processing on images, extracting the accumulated snow albedos of ground station positions, referring to corresponding documents, establishing a relation model of snow albedo and black carbon concentration, and performing inspection and repeated optimization on the relation model; processing the accumulated snow albedo images by using the relation model and acquiring the spatial and temporal distribution result of the black carbon concentration in accumulated snow by using research area vector boundary data interception. Compared with the conventional methods, the method employs the remote sensing technology and thus can obtain the spatial and temporal feature data of the black carbon concentration distribution in large-scale accumulated snow effectively.

The invention discloses a multifunctional remote alarm system which comprises a single chip computer, an induction alarm unit connected with the input end of the single chip computer, an alarm unit connected with the output end of the single chip computer, an automatic dialing unit and a voice broadcasting unit. The single chip computer is used for identifying alarm types, controlling the alarm to be connected with the single chip computer to conduct alarming, and controlling the automatic dialing unit to switch on an externally connected telephone set. Dialing is conducted according to a house owner number stored in a fixed phone mode in advance in the telephone set, the single chip computer controls a voice chip in the voice broadcasting unit to broadcast disaster types according to the alarm types. The multifunctional remote alarm system is comprehensive in function, simple in circuit, saving in alarm system resource, simple in executing step and high in operation reliability.

The invention discloses a fire protection method for a battery inn used for electric automobile battery charging. The fire protection method is characterized in that the battery temperature, flames ofbattery faults and the smoke amount of battery faults are monitored, and when the battery temperature is larger than a preset temperature value, the step of spraying fire-fighting media to a batteryis executed; when only one of three conditions that the battery temperature is between the preset temperature value and a limiting temperature value, a flame sensor sends out alarms and a smoke sensorsends out alarms is satisfied, the step of taking out a tray carrying the detected battery from the battery inn is executed; and when any two of the three conditions that the battery temperature reaches or exceeds the limiting temperature value, the flame sensor sends out alarms and the smoke sensor sends out alarms, the step of popping up the tray carrying the detected battery out of the batteryinn is executed. The method has the advantages that the execution of steps is simple, battery charging faults can be timely responded, and economic loss of battery charging faults can be reduced.

The invention provides a method, device and equipment for executing a machine learning task and a computer storage medium, relating to the field of cloud computing. The method comprises the steps thatafter a server side obtains a machine learning task, determining a basic mirror image; determining a container mirror image corresponding to the basic mirror image, and obtaining the container mirrorimage corresponding to the machine learning task from the container mirror image as a creation mirror image; utilizing the basic mirror image to create a virtual machine in a cloud server, and utilizing the creation mirror image to create a container instance in the virtual machine; and after mounting data corresponding to the machine learning task to the container instance, starting the container instance to start to execute the machine learning task. The execution steps of the machine learning task can be simplified, and the execution efficiency of the machine learning task is improved.

The invention relates to a remote sensing estimation method for the black carbon concentration in accumulated snow. The method performs regional scale black carbon concentration estimation based on the combination of MODIS daily accumulated snow synthetic products (MOD10A1 and MYD10A1) with a 500 meter spatial resolution and actually-measured black carbon concentration data of ground stations. The method comprises the steps of performing image fusion, map projection conversion and data format conversion on the MODIS daily accumulated snow products to acquire research area accumulated snow albedo data; performing cloud-removing synthesizing processing on images, extracting the accumulated snow albedos of ground station positions, referring to corresponding documents, establishing a relation model of snow albedo and black carbon concentration, and performing inspection and repeated optimization on the relation model; processing the accumulated snow albedo images by using the relation model and acquiring the spatial and temporal distribution result of the black carbon concentration in accumulated snow by using research area vector boundary data interception. Compared with the conventional methods, the method employs the remote sensing technology and thus can obtain the spatial and temporal feature data of the black carbon concentration distribution in large-scale accumulated snow effectively.

The invention provides a cup dropping device and a lid dropping device for an automatic fruit juice vending machine, aiming to solve the problem that the structures of the cup dropping device and the lid dropping device are relatively complicated in the prior art. The cup dropping device includes a cup barrel, a drive assembly and two dials; the cup barrel is provided with two oppositely set aside grooves; the dial is composed of a roller and picks evenly distributed on the outer wall of the roller, and the roller and the drive assembly Connected; the two dials correspond to the dialing slots one by one. The cover drop device includes a cup cover tube, a drive assembly and two dials; two oppositely arranged pull-off grooves are arranged on the side wall of the lower end of the cup cover tube; It consists of a plurality of paddles, and the rollers are connected with the drive assembly; the two dials are respectively arranged on both sides of the cup lid cylinder and correspond to the pull-out slots one by one. In the present invention, the juice cup or the cup cover can be smoothly removed by two dial wheels, and the overall structure is simplified.

The invention discloses a Car Service interface calling method and a vehicle. The method comprises the following steps that a CarMainManager.java is newly added between a Car APP (Application) and a Car.java, and the CarMainManager.java is added between the CarMainManager.java and the CarMainManager.java; the method comprises the following steps of: obtaining various types of API (Application Program Interface) Managers by CarMainManager.java through Car.java, and then providing the obtained various types of API Managers to each Car APP (Application Program). According to the method and the device, the execution step of calling the Car API by the Car APP is simplified, so that the APP code for calling the CarService interface is simple, the coding efficiency is improved, and the development efficiency is improved. In addition, the CarMainManager uses a single example mode to provide an instance object externally, so that only one CarMainManager.java object and one Car.java object exist in a system memory, system resources can be saved, and the performance of the system can be improved in some object use scenes needing to be frequently created and destroyed.

The invention provides a capping device for an automatic fruit juicing vending machine, and aims to solve the problem that a capping device in the prior art is complex in structure. The capping devicefor the automatic fruit juicing vending machine comprises a cup falling assembly, a cap falling assembly, a cap pressing assembly and a transferring assembly. The cup falling assembly comprises a cupbarrel, a driving assembly and two poking wheels; and the side wall of the lower end of the cup barrel is provided with two opposite poking grooves. The cap falling assembly comprises a cup cap cylinder, a driving assembly and two poking wheels; and the side wall of the lower end of the cup cap cylinder is provided with two opposite poking grooves. The cap pressing assembly comprises a driving mechanism and a pressing plate, and the driving mechanism drives the pressing plate to press downwards and move upwards to reset. The transfer assembly comprises a rotary disc motor, a rotary disc and acup base; and the cup base is driven by the rotary disc to sequentially pass through a cup falling station, a cover falling station, a cover pressing station and a cup taking station. The cup fallingassembly and the cap falling assembly are of a novel structure, and compared with an existing cover sealing device, the cup falling assembly and the cap falling assembly are simplified in structure.

The invention relates to a shale oil and gas combustion extraction method based on a multi-source time sequence remote sensing image, and the method employs a large amount of multi-source long-time sequence optical remote sensing data in a combined manner, improves the robustness of remote sensing image detection through higher space and time resolution, greatly improves the monitoring capability of shale oil and gas combustion, and the spatial and temporal distribution of large-area shale oil and gas can be quickly and automatically identified. The method is simple and feasible in execution steps, and the shale oil and gas combustion effect in an extraction area and even the whole world is good. According to the method, long-time and large-space-coverage optical image data are used, an optimized and concise thermal anomaly index is utilized, and accurate extraction of shale oil and gas combustion on a large space scale is achieved. According to the method, a detailed shale oil and gas combustion position which can be updated timely and effectively can be compiled, and meanwhile scientific reference can be provided for shale oil and gas combustion management and evaluation of the potential influence of shale oil and gas combustion on the atmospheric environment in China.

The invention provides a capping device for an automatic fruit juicer and vending machine, aiming to solve the problem of complex structure of the capping device in the prior art. The capping device for the automatic fruit juice vending machine includes a drop cup assembly, a drop cap assembly, a press assembly and a transfer assembly; the drop cup assembly includes a cup barrel, a drive assembly and two dial wheels; Two oppositely arranged detachment grooves; the drop cover assembly includes a cup lid cylinder, a driving assembly and two dial wheels; two oppositely arranged detachment grooves are arranged on the side wall of the lower end of the cup lid cylinder; the gland assembly includes a driving mechanism and the pressure plate, the drive mechanism drives the pressure plate to press down and move up to reset; the transfer assembly includes the turntable motor, turntable and cup holder; the cup holder passes through the cup dropping station, cap dropping station, capping station and taking out in turn driven by the turntable cup station. The cup dropping assembly and the cap dropping assembly in the present invention adopt a novel structure. Compared with the existing capping device, the structure of the cup dropping assembly and the cap dropping assembly in the present invention is simplified.

The present invention discloses a method for executing a program and an apparatus for executing a program. The method includes: obtaining a related operation item of an object to be operated, and displaying, on a display screen, an operation icon corresponding to the related operation item, where the object to be operated is a computer program operable by a user on the display screen, and a direction of pointing from an original display coordinate of the object to be operated towards a display coordinate of the operation icon is an operation icon direction; according to the original display coordinate of the object to be operated and a display coordinate of the object after being dragged by the user, calculating a movement direction of the object to be operated; and starting to execute a functional operation corresponding to the operation icon when it is detected that the movement direction of the object to be operated is the same as the operation icon direction. The embodiments of the present invention can simplify steps of executing a computer program, and make operations intuitive and natural.

The invention discloses an iceberg remote sensing recognition method based on a random forest algorithm. According to the method, SAR image data provided by sentinel-1A is adopted to recognize a sea ice mountain, and the method mainly comprises the steps that threshold segmentation is performed on a preprocessed SAR image, background elements are removed, and then sample features are selected according to prior knowledge. And meanwhile, ice mountain and ice mountain-like training samples are selected in an object-oriented mode. The suspected iceberg samples to be classified are processed in asimilar mode, but are completely exported without being selected. And then, the method has the steps of carrying out Min-Max data standardization on all the obtained samples, and finally training therandom forest model by using the generated training data, and using the trained model for classification of to-be-classified samples to obtain a final classification result, thereby realizing identification of the iceberg.

The invention relates to a remote sensing classification method for sea ice types, which uses satellite radar altimeter Cryosat-2 data to classify polar sea ice, and realizes sea ice classification based on a new method and on a large scale. The steps include obtaining the latitude and longitude coordinates of the measurement point and the corresponding radar echo waveform from the CryoSat-2 altimeter data, extracting the relevant characteristics of the echo waveform; downloading the AARI sea ice type data, and extracting the sea ice type information at the corresponding measurement point ;Perform geographic matching on the above-mentioned extracted data information, and convert it into point data with latitude and longitude coordinates through MATLAB programming; the waveform features at the obtained points and the corresponding sea ice types are used as training data, and the random forest classifier is used for For training, the sea ice classification is carried out on the data to be classified; the classified data are processed in ArcGIS through projection transformation, gridding, etc., and a sea ice type data set with a spatial resolution of 25km is obtained.

The invention relates to an estimation method for the volume change of a subglacial lake. The estimation method comprises the steps that L1B waveform data in an SARIn mode of a CryoSat-2 radar altimeter in the corresponding time period are obtained; the surface elevation of a subglacial lake area is calculated through a waveform re-tracking method; obtained surface elevation data are pretreated toremove elevation change anomaly points; the pretreated elevation data are subjected to slope correction through a DEM to remove the error caused by the slope; 100*100 m of grids are finally generatedthrough kriging interpolation, then the elevation change in the corresponding time period is calculated, back scattering energy is added into elevation change values for correction, and the influenceof the back scattering energy to the elevation change is eliminated; and the shape and area of the subglacial lake are obtained through the elevation change values, the elevation change values of thesurface of the subglacial lake of each grid are integrated, and finally the volume change of the subglacial lake in the corresponding time period is obtained. According to the estimation method, fluctuation of the surface of the subglacial lake can be accurately and effectively reflected, and thus the volume change of the subglacial lake is estimated.