38 results about "Cross model" patented technology

The invention relates to the field of data search and provides a cross-model method for searching for a 3D model with 2D pictures. The method comprises following steps: 1) establishing a 3D model library; 2) extracting characteristic vectors; 3) training convolutional neural networks; 4) inputting the characteristic vectors; 5) completing matching retrieval. According to the method, 3D objects and 2D pictures are projected into a new space for measuring the similarity of 3D and 2D; therefore, the problem that the similarity of 3D and 2D data cannot be measured and retrieved due to different data formats is solved; at the same time, the invention also provides an end to end solution scheme which is more efficient than other traditional frames and has better real-time performance.

The invention discloses a cross-model Hash retrieval method on the basis of cooperative training and matrix decomposition. By the aid of the cross-model Hash retrieval method, the similarity between models and the internal similarity of the models can be effectively constrained for unlabeled cross-model data. The cross-model Hash retrieval method includes implementation steps of acquiring original data and carrying out normalization processing on the original data; carrying out cooperative training to obtain constraints between the models; acquiring internal constraints of the models by the aid of neighbor relations; decomposing training data matrixes and adding the constraints between the models and the internal constraints of the models into the training data matrixes to obtain objective functions; carrying out alternate iteration to obtain expressions of basis matrixes, coefficient matrixes and projection matrixes; carrying out quantization to obtain Hash codes of training data sets and test data sets; computing the Hamming distances between every two Hash codes of the data sets; sorting the Hamming distances to obtain retrieval results. The cross-model Hash retrieval method has the advantages that constraints on the similarity between the models of the cross-model data can be obtained by the aid of cooperative training processes, accordingly, the image and text mutual retrieval performance can be improved, and the cross-model Hash retrieval method can be used for picture and text mutual search service of mobile equipment, internets of things and electronic commerce.

It is a structure module amendment method using a cross-modal cross-model, by adjusting the stiffness matrix and the quality matrix of finite element model to make the modal frequencies and mode through calculation match with the actual structure. Therefore for each unit of the finite element model, the stiffness matrix and the quality matrix coefficients have two amendments. Through the comparison of the structural finite element numerical model and experimental actual model, get the correction coefficient of each module, and thus amend the stiffness matrix and quality matrix to achieve the model amendment purpose. The invention has both advantages of adjustment direct and indirect physical matrix without iteration, improving work efficiency. It also can maintain the physical contact between structural models. In addition, the measurement mode required in the method does not require a return of the quality. Combined with the modal parameter identification technologies based on the output response, it can amend the offshore structure model in environment incentives. So the method has more practical value.

In one embodiment, a computer program product for creating a configuration template for a set of devices includes a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code including computer readable program code configured for determining command information for a plurality of devices, computer readable program code configured for identifying a command structure from the command information which is common to a set of devices from the plurality of devices, and computer readable program code configured for associating the set of devices to a common configuration template. In another embodiment, a method for creating a configuration template for a set of devices includes determining command information for a plurality of devices, identifying a command structure from the command information which is common to a set of devices from the plurality of devices, and associating the set of devices to a common configuration template.

The invention discloses a method for automatically recovering cross-model GUI (graphic user interface) test scripts, which is used for carrying out automatic recovery on GUI test scripts recorded on an older-version GUI program aiming at a new-version GUI program. The invention provides a method implemented by using the complementation of two event reachability models so as to describe the GUI structure and event reachability models of an application program more completely and accurately, the legitimacy of statements of the GUI test scripts is examined by using the two event reachability models, and an automatic recovery scheme is given to incorrect GUI test scripts in the new-version GUI program. According to the invention, the legitimacy verification and recovery of scripts are completed by using the collaboration of the two models, and a self-built event reachability model is continuously perfected in the process of recovering without the overmuch confirmations of engineers; and due to the joint analysis and verification of the two models, the integral description on all event flows included in the GUI application program is ensured, and the automation of legitimacy verification and recovery of GUI test scripts is realized.

The invention discloses a mechanism movement accuracy reliability analysis method based on a fuzzy out-crossing model. The mechanism movement accuracy reliability analysis method includes the steps of (1) building a generalized fuzzy random stress-strength interference model (please see the specifications for the model) according to task characteristics, (2) determining a subordinating degree function mu(x) of movement errors, (3) determining the reliability R(tau0) at the moment tau0, and calculating the complete up-crossing rate v+(tau) and the complete down-crossing rate v-(tau), and (4) calculating the fuzzy time-variation reliability R in the mechanism task executing process. By means of the mechanism movement accuracy reliability analysis method, influences of the errors and tolerances of mechanism movement on the mechanism accuracy reliability are considered, a time-variation reliability calculation method-PHI2 and a state fuzzy analysis method are combined, and the mechanism fuzzy time-variation reliability problem can be effectively solved; the aim that in a classical mechanism movement reliability theory, when the time-variation performance and the fuzzy performance are considered at the same time, the failure probability is calculated by properly changing the out-crossing model is achieved.

A system and method facilitating speech detection and / or enhancement utilizing audio / video fusion is provided. The present invention fuses audio and video in a probabilistic generative model that implements cross-model, self-supervised learning, enabling rapid adaptation to audio visual data. The system can learn to detect and enhance speech in noise given only a short (e.g., 30 second) sequence of audio-visual data. In addition, it automatically learns to track the lips as they move around in the video.

The invention provides a calculation method of a pipe joint hoop strain of a tide load sinking pipe tunnel. The method includes steps of, assuming a back silt layer on the pipe joint as an impervious bed, and regarding the change of the tide level as a large area load pO added on the impervious bed, wherein the location of an underground level is the top face of the impervious bed; not considering about influence of tide on the pipe joint structure, calculating water, soil pressure and subgrade reaction acted on the outer wall of the pipe joint; applying a winkler foundation module, regarding the loop strain calculation as the plane strain problem; analyzing the loop stress and deformation of the pipe joint structure by a load-structure method; through the calculation of cross model stress of the pipe joint, acquiring the relationship of the loop stress strain relationship of the pipe joint; finally, through calculation, acquiring the loop strain distribution of inner and outer walls of the pipe joint under one tide level and influence of the loop strain of every point of inner and outer walls of the pipe joint along with the change of the tide level. The calculation result can be used for predicting the loop strain of the pipe joint of the sinking pipe tunnel in operation stage, judging the part where may generate crack, and carrying out key monitoring and prevention.

The invention discloses a method for detecting scouring depths of a soil body around a marine pile foundation. The method comprises the steps: (1) a pile-soil system is built; (2) the pile foundationis divided into n joints through a concentrated mass method to be numbered, the joints are connected through massless elastic rods with the length being d, each joint and a lower connecting rod serveas a unit, and the rod length d serves as the unit thickness; (3) the soil body around the foundation is layered, the thickness of each layer is the same as the unit thickness, namely d, the soil bodyaround the foundation is simplified to be massless spring constraint around the joints, and the elastic coefficient is determined; (4) an overall rigidity matrix and a mass matrix under the pile-soilsystem are built; (5) the inherent frequency and vibration modes of all orders of the pile foundation under the different scouring depths are detected; and (6) the rigidity correction coefficient isobtained through a cross-model and cross-mode method (CMCM method), the joints, namely damaged units, corresponding to mutation positions of the correction coefficient are found, the number of the units between the damaged units and pile foundation units on the mud surface is determined, and the range of the scouring depths is determined by multiplying the number of the units and the unit thickness.

Cross database model datum access with semantic preservation is provided. Data stored in a database under a particular database model can typically be inaccessible or not interoperable with data stored in another database model. A first datum of a first database model is transformed to an interim datum of an interim database model while preserving the data semantics associated with the first datum. Further, the second datum can be transformed into a third datum associated with a third database model, again while preserving the semantics. As such, data in a first silo can be accessed in a different silo while retaining semantic relationships. Further, the use of an interim database can reduce the processing needed to accomplish transforms between a planarity of database models.

Presenting data from different data providers in a correlated fashion. The method includes performing a first query on a first data set controlled by a first entity to capture a first set of data results. The method further includes performing a second query on a second data set controlled by a second entity to capture a second set of data results. The method includes receiving a selection of one or more results from the first data set. The method further includes using the one or more selected results, consulting a relationship ontology that correlates data stored in different data stores controlled by different entities, to identify one or more relationships between data in the selected results set and the second data set.

The invention discloses a multi-particle hybrid modified thrombus simulation method based on a Cross model. A multi-particle hybrid modified SPH method based on the Cross model is utilized to simulatethe blood, so a problem that the phenomenon that large-mass particles sinks downwards and small-mass particles rise upwards in the simulation process does not conform to the normal blood physiological phenomenon is solved, a particle-by-particle polymerization method is utilized to simplify a thrombus model to simulate thrombus formation, and a problem that a traditional method can not simulate thrombus formation of the blood is solved. The method is advantaged in that the blood can be more realistically simulated, and thrombus formation of the blood can be further simulated. Through correctly simulating thrombus formation, the thrombus study is facilitated, the method can be applied to medical applications such as virtual surgery and medical assistant research, moreover, needs of relatedaspects in game and film industries can be satisfied.

It is a structure module amendment method using a cross-modal cross-model, by adjusting the stiffness matrix and the quality matrix of finite element model to make the modal frequencies and mode through calculation match with the actual structure. Therefore for each unit of the finite element model, the stiffness matrix and the quality matrix coefficients have two amendments. Through the comparison of the structural finite element numerical model and experimental actual model, get the correction coefficient of each module, and thus amend the stiffness matrix and quality matrix to achieve the model amendment purpose. The invention has both advantages of adjustment direct and indirect physical matrix without iteration, improving work efficiency. It also can maintain the physical contact between structural models. In addition, the measurement mode required in the method does not require a return of the quality. Combined with the modal parameter identification technologies based on the output response, it can amend the offshore structure model in environment incentives. So the method has more practical value.

The invention discloses equipment for monitoring the scouring depth of a pile foundation in real time and a monitoring method of the equipment. The monitoring equipment comprises a sensor group, a data acquisition instrument, data processing equipment, a solar panel, a storage battery and excitation equipment. In specific implementation, the method comprises the steps that excitation is applied to a pile foundation through excitation equipment, and after actual measurement modes of the pile foundation are obtained through induction, collection and data processing equipment, and a cross model cross mode equation is constructed in combination with corresponding finite element numerical model modes; and the soil body unit damage number is identified through the unit rigidity correction coefficient alpha n of the equation, and further the scouring depth around the pile foundation is acquired. The purpose of monitoring the pile foundation scouring depth on water can be achieved, meanwhile, the scouring depth change situation in the whole service life after the pile foundation is put into production can be monitored in real time, the problem that the scouring depth is difficult to monitor through traditional manual diving is solved, and the potential risks caused by the fact that the pile foundation scouring depth is uncertain are avoided; besides, the method has the advantages of good operability, labor saving, strong adaptability and the like.

The invention discloses an RSM-Kriging-GA algorithm based energy consumption optimizing method and system for an air conditioning system in a wide region. The method comprises the following steps: reading current course arrangement, and setting start and stop of an air conditioner according to the course arrangement; automatically selecting a corresponding season mode according to the date on thatday, and obtaining historical data under the corresponding season mode; adopting an RSM cross model to fit to a relationship among number of people attending the source, an environment temperature, aclassroom size and a real-time refrigeration equivalent in the historical data; obtaining current environment parameters in real time, and calculating needed refrigeration equivalent according to theRSM cross model in real time; constructing a constraint relationship, and adopting a Kriging algorithm to establish a mathematic model between the environment parameters and energy consumption E; solving the optimal parameter solution based on a GA algorithm, and performing energy consumption optimizing automatic control on a set temperature, air speed and refrigeration time length according to the optimal parameters. The RSM model is based to fit to the historical big data, so that a constraint model is constructed, and a wide region air conditioning system energy consumption optimizing model based on the RSM-Kriging-GA algorithm is constructed, and therefore, air conditioner energy consumption is optimized, and resources are saved.

The invention discloses a DEA cross model energy efficiency analysis method based on principal component fusion. The method comprises the following steps: obtaining 20 groups of production data of a PTA (purified terephthalic acid ) production device; obtaining input indexes of a phthalic acid production device according to the 20 groups of production data, wherein the input indexes comprise 17 factors influencing acetic acid consumption; obtaining a hierarchical model of the 17 factors according to a preset interpretative structural model; according to a preset analytic hierarchy process andthe hierarchical model, forming fusion data; and obtaining output indexes according to a preset data envelopment analysis cross model and the fusion data, wherein the output indexes comprise tower topconductivity. The method optimizes input data of the data envelopment analysis cross model, and improves distinction degree of analysis results; and besides, by carrying out analysis and evaluation on production efficiency of the PTA production device, relative effectiveness of the production efficiency is obtained, so that energy saving and consumption reducing direction of the PTA production device is obtained, and meanwhile, effectiveness and applicability of the analysis conclusion above can be proved.

The invention discloses an image scrambling evaluation method and device, belonging to the field of digital image processing. The method includes: respectively performing bitwise layering on the original image and at least one scrambled image, obtaining a bitmap image of the original image and a bitmap image of the at least one scrambled image; according to the cross-cortical neural network A model that extracts features from the bitmap image of the original image and the bitmap image of the at least one scrambled image to obtain the structural feature sequence of the original image and the structural feature of the at least one scrambled image Sequence: calculating according to the structural feature sequence of the original image and the structural feature sequence of the at least one scrambled image to obtain the scrambling degree of the at least one scrambled image. The present invention realizes the direct extraction of structural feature information of the image by layering the original image and at least one scrambled image by bit and using a cross-cortical neural network model to perform feature extraction, thereby better evaluating the scrambling degree.

There is a need for solutions for more efficient predictive data analysis systems. This need can be addressed, for example, by a system configured to obtain, for each predictive task of a plurality of predictive tasks, a plurality of per-model inferences; generate, for each predictive task, a cross-model prediction based on the plurality of per-model inferences for the predictive task; and generate, based on each cross-model prediction associated with a predictive task, a cross-prediction for the particular predictive task, wherein determining the cross-prediction comprises applying one or more probabilistic updates to the cross-model prediction for the particular predictive task and each probabilistic update is determined based on the cross-model prediction for a related predictive task of the one or more related predictive tasks.

The invention discloses a cross-model Hash retrieval method on the basis of cooperative training and matrix decomposition. By the aid of the cross-model Hash retrieval method, the similarity between models and the internal similarity of the models can be effectively constrained for unlabeled cross-model data. The cross-model Hash retrieval method includes implementation steps of acquiring original data and carrying out normalization processing on the original data; carrying out cooperative training to obtain constraints between the models; acquiring internal constraints of the models by the aid of neighbor relations; decomposing training data matrixes and adding the constraints between the models and the internal constraints of the models into the training data matrixes to obtain objective functions; carrying out alternate iteration to obtain expressions of basis matrixes, coefficient matrixes and projection matrixes; carrying out quantization to obtain Hash codes of training data sets and test data sets; computing the Hamming distances between every two Hash codes of the data sets; sorting the Hamming distances to obtain retrieval results. The cross-model Hash retrieval method has the advantages that constraints on the similarity between the models of the cross-model data can be obtained by the aid of cooperative training processes, accordingly, the image and text mutual retrieval performance can be improved, and the cross-model Hash retrieval method can be used for picture and text mutual search service of mobile equipment, internets of things and electronic commerce.

The invention relates to big data, and provides a data processing method and device, a computer readable storage medium and computer equipment, and the method comprises the steps: inputting a first dimension reduction feature into a trained feature cross model, and obtaining at least one target dimension reduction feature pair; inputting each target dimension reduction feature pair into a trainedweight calculation model to obtain first weight information corresponding to each target dimension reduction feature pair; inputting the first weight information and the second dimension reduction feature into a trained weighting model, and outputting second weight information corresponding to the second dimension reduction feature; sorting the object data according to the second weight information and generating a corresponding object data sequence, and sending the object data sequence to the corresponding terminal, so that the terminal displays the object data in sequence according to the object data sequence, the accurate object data sequence can be obtained by processing the features, the corresponding object data is displayed according to the object data sequence, and the accuracy ofobject data display is improved.

The invention relates to a crossing model considering internal cost and supporting rapid way finding. The crossing model adopts a cellular node model, and has a three-layer structure comprising an outermost layer, a middle layer and an innermost layer; the outermost layer is an interface layer and is a dynamic expansion layer, and the quantity of the interfaces of the outermost layer is increased or decreased in the road network logicalization process, wherein the interfaces are divided into incoming interfaces and outgoing interfaces, and are used for preserving all topology connection relation information of one node and other nodes; the middle layer is a channel layer, is a logic layer and is used for indicating correspondence of the interfaces to practical roads; and the innermost layer is an internal cost layer, and is used for preserving the internal connection cost of crossings. The crossing model fully considers the internal passing costs of the crossings, solves the problems of low way finding speed and inconsistence of the way finding result with the practical driving road, and can be used to construct vehicle navigation electronic maps.

The invention relates to a short-circuit calculation and simulation method for a ship's AC-DC hybrid power system, which can perform short-circuit calculation and simulation on the ship's AC-DC hybrid power system. The invention includes detecting the endpoint coordinates of each component in the drawn network diagram, and assigning respective ID numbers to each component as the basis for judging the connection; according to the connection status of the components, the obtained connection relationship of each component is converted into digital information, and the information is displayed in the form The form is stored in the database; calculate the short-circuit current of the generator: calculate the short-circuit current of the battery: calculate the short-circuit current of the inductance element; calculate the short-circuit current of the DC motor; judge the position of the short-circuit point, and correct the current. The present invention does not have the model and algorithm of the AC-DC hybrid system, and the steps are more convenient.

The invention relates to a crossing model considering internal cost and supporting rapid way finding. The crossing model adopts a cellular node model, and has a three-layer structure comprising an outermost layer, a middle layer and an innermost layer; the outermost layer is an interface layer and is a dynamic expansion layer, and the quantity of the interfaces of the outermost layer is increased or decreased in the road network logicalization process, wherein the interfaces are divided into incoming interfaces and outgoing interfaces, and are used for preserving all topology connection relation information of one node and other nodes; the middle layer is a channel layer, is a logic layer and is used for indicating correspondence of the interfaces to practical roads; and the innermost layer is an internal cost layer, and is used for preserving the internal connection cost of crossings. The crossing model fully considers the internal passing costs of the crossings, solves the problems of low way finding speed and inconsistence of the way finding result with the practical driving road, and can be used to construct vehicle navigation electronic maps.

A novel dynamic-road-network-based traffic guidance method includes: intelligent cameras acquire road condition information of traffic crossings in real time, including speed and vehicle number; each crossing is subjected to real-time traffic flow modeling by a modified hydromechanics-based traffic flow model; time periods of vehicles passing the crossings are converted into network transmission delay according to the crossing models; shortcut querying is performed by means of delay routing; the vehicles are guided with optimal driving paths. Real-time traffic flow modeling is based on the crossing intelligent cameras, and accordingly the shortcut querying method based on the delay routing mechanism is realized and real-time traffic guidance is realized.

The invention discloses a design method of a fan sound insulation cover. The design method comprises the following steps: a, establishing a fan sound insulation cover body quantity model; b, establishing parameterized basic unit roof panel and shingle plate models; c, checking collision after the basic unit roof panel and wall panel plate models are assembled to the overall mass model in a simulated mode, and judging whether a design scheme is feasible or not according to the simulated assembly condition; and d, integrating the integral model without errors in simulation assembly with other cross models, and checking whether the integral model conflicts or not. The fan sound insulation cover design method is designed based on a building information model, the working efficiency is effectively improved, and the error rate of procedures such as drawing design, machining and manufacturing and on-site construction and installation is reduced.