169 results about "Characteristic type" patented technology

The present invention permits backup processing suited to data characteristics relating to backup target data by means of a method that is simple for the user. Data characteristic classification definition information, in which data characteristic IDs correspond with one or more data characteristic types respectively, and mapping information, in which backup destination server information corresponds with one or more data characteristic IDs respectively, are prepared. The backup source server 3 sets data characteristic IDs in each of the backup target files on the basis of metadata of designated backup target files and of the data characteristic classification definition information, and then determines backup destination servers 6A to 6C for each of the backup target files on the basis of the set data characteristic IDs and mapping information and transmits the backup target files to the determined servers 6A to 6C.

The invention discloses a target detection algorithm based on intelligent equipment sensor data fusion and deep learning. Through fused radar point cloud data and camera data, data feature types capable of being sensed by a detection model are enriched. By performing model training on data channel fusion with different configuration, optimal channel configuration is selected, detection accuracy isimproved, and meanwhile calculation power consumption is lowered. By performing a test on real data, the channel configuration suitable for a real condition is determined, and the goals of processingfusion data by use of a Yolo deep convolutional neural network model and performing target barrier detection on a road scene is achieved.

The invention discloses a method for determining a network interoperable mode and terminal equipment which are used for solving the problems that the time for call ringing and waiting is long, and the probability for call drop and the electric power consumption are increased because the terminal is subjected to frequently reselection among different networks in the prior art. The method is applied to the terminal which supports the LTE (Long Term Evolution) access technology, and supports at least one of 2G (2nd Generation) access technology and 3G (3rd Generation) access technology. The method comprises the following steps of: when the terminal accesses a network, determining whether a network side supports a CS (Circuit Switch) fallback mode or not; when the network side is determined to support the CS fallback mode, and the characteristic type of the settings of the network side gives priority to voice, determining to prefer to dwelling at a 2G network or a 3G network; when data service is carried out under the condition of dwelling at the 2G network or the 3G network, determining whether the reselection to an LTE network is needed or not; and when the terminal determines to reselect to the LTE network, reselecting to the LTE network and executing the data service, and returning to the 2G network or the 3G network after the data service is finished.

Apparatus and methods of revealing the hierarchical structure of a document having content of a characteristic type of content are described (100). The hierarchical structure may be expressed, independently of document content type, as a tree structure of one or more nodes (126) A semantic representation for interpreting the tree structure may also be provided, document description files are used to encapsulate structural and meta information associated with a document stored on a computer-readable medium (156). Document description files are external to native application files and have a set of required fields. Document description files point to the referenced document data using uniform resource locators (URLS) and serve as virtual documents. In addition to the required fields, applications can choose to encode additional structural information in the document description files.

The invention discloses a multi-feature mobile terminal malicious software detecting method based on network flow and a multi-feature mobile terminal malicious software detecting system based on the network flow. The method comprises the following steps of: extracting features capable of effectively representing mobile terminal malicious software network behaviors from network flow data; classifying the extracted features capable of effectively representing the mobile terminal malicious software network behaviors according to different feature types; building detecting models adapting to the classified features, wherein each kind of types has one corresponding unique detecting model; and selecting the corresponding detecting model for each kind of features, and outputting the corresponding detecting result. By aiming at different feature types of the mobile terminal network flow, the detecting models adapting to different feature types are designed; a user can select the required model by the self according to requirements; the detecting accuracy can be improved to a certain degree through different detecting models designed by aiming at different feature types; and the individualized requirements of the user are met.

The present invention provides a solution for predicting an advertisement click-through rate. The solution comprises: acquiring characteristic related information of multiple characteristic types related to multiple past delivered advertisements in a predetermined past time period; performing cross combination on characteristic related information of at least two characteristic types of each past delivered advertisement, to determine multiple cross characteristic sets, and calculating to determine cross characteristic identifiers separately corresponding to the multiple cross characteristic sets; extracting an advertisement display quantity and an advertisement click quantity corresponding to each cross characteristic set, and calculating to determine an advertisement click-through rate corresponding to each cross characteristic set, so as to use the advertisement click-through rate as a cross characteristic value; performing training on a logistic regression model based on the cross characteristic identifiers and the cross characteristic values separately corresponding to the multiple cross characteristic sets, and calculating to determine a model training parameter; and performing prediction calculation on an advertisement click-through rate of a to-be-predicted advertisement based on the model training parameter. According to the solution, more reliable training data is provided for prediction calculation of an advertisement, so that accuracy of a prediction calculation result of an advertisement click-through rate is ensured.

Embodiments of the present invention recite a method and system for implementing a Geographic Information Systems (GIS) network. In one embodiment, configuration data comprising a unique identification of a mobile electronic device and an assigned membership of the mobile electronic device to a workgroup is received. The method further comprises selecting a data dictionary comprising at least one desired GIS feature type which was not originally intended for use by the mobile electronic device based upon the assigned membership of the mobile electronic device to the workgroup. The method further comprises sending the data dictionary to the mobile electronic device via a wireless communication network.

The invention provides an identification method of the machining characteristics of complex parts of an airplane, which comprises steps of: firstly, setting a machining coordinate system, identifying a machining surface and preprocessing a hole to complete basic information process; secondly, layering and intersecting to obtain intersecting line rings in each layer of intersecting result and relationships among the intersecting line rings to complete the construction of outline rings of generalized grooves; building the generalized grooves according to the outlines of the generalized grooves and the source surface depended by the intersecting lines; building the characteristics relevance tree of the generalized grooves according to the lengthways relationship of the outlines of the generalized grooves; and emerging the generalized grooves and identifying the characteristics types to complete the identification of the machining characteristics of a whole part. The method has the characteristics of high identification accuracy rate, high speed and small space usage, and the like; can be used for designing and developing systems for programming the complex parts of the airplane by means of intelligent numerical control, analyzing a machining technical scheme, and automatically generating blanks, and the like; and has good application foreground.

As a unit element for defining a describing procedure for description of a feature data characteristic of the content of a video data, a descriptor is formed in a description format structured to have its attribute as lower-level element and which may include other descriptor as attribute. That is, the description format for the descriptor consists of a feature indicative of a descriptor or attribute as lower level element, and a feature type indicative of the data type of the feature.

The embodiment of the invention discloses an electrocardiogram signal processing method and device. The method comprises the steps of denoising sample data including a reference characteristic type electrocardiogram signal to obtain a filter electrocardiogram signal, wherein the sample data includes sample data for training and sample data for test, extracting characteristics of the filter electrocardiogram signal on the basis of a multi-electrocardiogram period fusion method to obtain a characteristic electrocardiogram signal, carrying out data normalization treatment on the characteristic electrocardiogram signal to obtain a standard electrocardiogram signal, training a BP neural network according to the standard electrocardiogram signal corresponding to the sample data for training to obtain a trained BP neural network, injecting the standard electrocardiogram signal corresponding to the sample data for test into the trained BP neural network, and acquiring a classification result of a standard signal corresponding to the sample data for test. By adopting the electrocardiogram signal processing method and device disclosed by the embodiment, the comprehensiveness and accuracy for extracting and classifying the characteristic electrocardiogram signals can be improved.

The invention discloses an aircraft structural part cutting parameter optimization method based on characteristics. The method provides a cutting parameter optimization model based on characteristics and gives full consideration to problems of clamping, feed strategies, characteristic types, characteristic structures and cutting strategies. The method uses a machine tool, a workpiece material and a cutter as restraints, uses efficiency, processing quality and cost as optimization goals, and uses rotating speed, feed, cutting depth and cutting width as optimization factors to build the model, and cutting parameter optimization is achieved through a genetic algorithm. The method can solve the problem that aircraft structural part processing parameters at present are too conservative, can greatly improve efficiency, and simultaneously can avoid the problem that deformation occurs easily during processing, the position of a thin wall vibrates easily, and the cutter can be bounced easily at the position of a corner.

Methods, systems and apparatus are described to render a map with adaptive textures for map features. Embodiments may for a portion of map data, such as a map tile, including a feature of a given feature type specify a level-of-detail texture. A level-of-detail texture may be one of a plurality of level-of-detail textures for a given feature type ordered according to level-of-detail. Embodiments may then provide the specified level-of-detail texture with a mipmap chain to a rendering unit to render the map data. At the lowest level of the mipmap chain may be the specified level-of-detail texture. At the next lowest level of the mipmap chain may be a portion of the level-of-detail texture adjacent to the specified level-of-detail texture in the ordered plurality of level-of-detail textures for the feature type.

Embodiments of the present invention recite a method and system for implementing a Geographic Information Systems (GIS) network. In one embodiment, configuration data comprising a unique identification of a mobile electronic device and an assigned membership of the mobile electronic device to a workgroup is received. The method further comprises selecting a data dictionary comprising at least one desired GIS feature type which was not originally intended for use by the mobile electronic device based upon the assigned membership of the mobile electronic device to the workgroup. The method further comprises sending the data dictionary to the mobile electronic device via a wireless communication network.

Embodiments of the present invention recite a method and system for administrating GIS data dictionaries. In one embodiment, a mobile electronic device is assigned to a workgroup. The method further comprises selecting a data dictionary comprising at least one desired GIS feature type which was not originally intended for use by the mobile electronic device based upon the assigned membership of the mobile electronic device to the workgroup. The method further comprises sending the data dictionary to the mobile electronic device via a wireless communication network.

The invention discloses a three-dimensional process model evolution generation method applied to digitalized process design, which belongs to the field of digitalized manufacture. The method includes the following steps: building a manufacture characteristic type information base, obtaining product manufacture characteristic information by measuring and analyzing a product real object, conducting digitalized process design according to the product manufacture characteristic information, storing process decision results, constructing a three-dimensional process model generation rule base, determining a reversing generation flow of a three-dimensional process model from the product to a blank to finish evolution change of the three-dimensional process model. The method achieves automatic generation of the three-dimensional process model based on integration of process information and process engineering, is capable of improving the process model generation process and the efficiency, adopts a geometrical operation method without historical modeling in the generation process of the three-dimensional process model, supports various modeling software and improves geometrical calculation efficiency when the process model is generated.

Embodiments of the present invention recite a method and system for upgrading a legacy cellular device. In one embodiment, a GIS data collector application for enabling a cellular telephone to perform GIS data collector functions is installed upon a cellular telephone which is not originally intended to be used as a GIS data recording device. The method further comprises selecting a data dictionary comprising at least one desired GIS feature type which was not originally intended for use by the cellular telephone based upon an assigned membership of the cellular telephone to a workgroup. The method further comprises sending the data dictionary to the cellular telephone via a wireless communication network.

The invention provides a three-dimensional modeling system and method for prefabricated parts. The three-dimensional modeling system comprises a modeling rule maintenance module, a frame model base maintenance module, a whole machine parameterization modeling module and a three-dimensional model generation engine, wherein the whole machine parameterization modeling module is used for reading and analyzing to-be-built frame models of the prefabricated parts and modeling rules of the frame models in a frame model base, instantiating the frame models according to input part types, characteristic types and parameters, and building the parts and assembly models of the prefabricated parts; and the three-dimensional model generation engine is used for generating three-dimensional models of the prefabricated parts according to the built parts and assembly models of the prefabricated parts. According to the three-dimensional modeling system and method, the modeling rules and the frame models of the prefabricated parts are separated, the modeling rules of the prefabricated parts can be added and modified conveniently, and complete machine parameterization modeling meeting different design requirements as well as the three-dimensional models of the prefabricated parts can be generated rapidly through general and customizable part bases and the modeling rules.

Techniques are provided for selecting status data. Redundant views are obtained from multiple synchronous redundant devices. It is determined that the redundant views from the multiple synchronous redundant devices are conflicting. A redundant view score is calculated for each of the redundant views based on one or more characteristics from each of at least two characteristic types, wherein the characteristics are associated with weighted scores. One of the redundant views is selected based on the calculated redundant view score for each of the redundant views.

The invention discloses a public bicycle flow variation volume forecasting method based on heap model fusion. The public bicycle flow variation volume forecasting method comprises the steps of: 1, adopting a method of fusing public bicycle rental record data and meteorological data for extracting features, and constructing eigenvectors from several perspectives of time, space, meteorology, history, clustering and the like; 2, adopting a distance similarity matrix combining geological positions and a rental relation, clustering by utilizing a clustering algorithm, and configuring clustering features into the eigenvectors; 3, dividing the eigenvectors into five groups according to feature types, training five basic models by utilizing a machine learning system based on a gradient boosting tree algorithm, training features by adopting a cross validation method, and training a heap model by taking results of the five groups of basic models as features. The public bicycle flow variation volume forecasting method based on heap model fusion ensures that a certain difference exists among the basic models, constructs the heap model by adopting the cross validation method finally, improves the accuracy degree of the model, has good forecasting precision, and has small errors.

The invention discloses a method of super-dimensional river dynamics self-adaptive parallel monitoring, which includes the steps as following: input super-dimensional data into a system and classify according to the different dimension where the data are; create a super-dimensional unstructured grid river dynamics model based on a characteristic-type high-resolution numerical algorithm; in terms of an efficient parallel algorithm in a super-dimensional fluid splitting scheme, perform intra-dimensional and inter-dimensional calculations; the calculation region is divided into a plurality of sub-regions, each sub-region is mapped on a calculation node on the parallel system structure, the communication between the nodes uses a standard message passing interface, the overlapped parallel optimization technique of calculation and communication in the self-adaptive grid, and the calculation of variables associated with the space is independent. The method in the invention puts the super-dimensional river dynamics into the adaptive grid to execute the efficient parallel calculation of splitting scheme, and simultaneously processes the change of dimension; the method realizes the monitoring of river conveniently, timely and high accurately.

The invention discloses a calibration optimization method and system for speaking test evaluation. The method includes the steps of selecting part of all voice data corresponding to question types to be calibrated to serve as calibration voice data, conducting manual annotation by calibration specialists, obtaining the manual annotation result of the manually-annotated calibration voice data, conducting voice recognition on the calibration voice data through a voice recognition system, extracting evaluation characteristics of different characteristic types corresponding to evaluation standards of the question types to be calibrated from the voice recognition result of the calibration voice data, and training and optimizing existing marking models corresponding to the question types to be calibrated through the combination of the evaluation characteristics and the manual annotation result of the calibration voice data so as to obtain new marking models. Due to the fact that the existing marking models are optimized through the manual annotation result, the new marking models can be matched with the marking standards of existing speaking tests as much as possible, and the better marking performance can be presented when the speaking test evaluation is conducted through the new marking models obtained through the method.

The invention discloses an advertisement putting method. The method comprises the following steps of: obtaining click rate feature parameters of a predetermined history put advertisement in a predetermined history time period; crossly combining at least two types of feature parameters in the feature parameters to obtain a combined feature parameter, and digitalizing the feature parameters and thecombined feature parameter to obtain a feature parameter set; carrying out feature selection on the feature parameter set to obtain a target feature parameter; and training a prediction model on the basis of the target feature parameter, and carrying out prediction calculation on a click rate of a to-be-predicted advertisement through the prediction model. The invention furthermore provides an advertisement putting system. According to the method and system, in the advertisement click rate prediction process, the feature parameters are combined and digitalized, and then feature selection is carried out on the feature parameters to improve the feature selection quality, so that the condition of mistakenly deleting features of all the information amounts can be avoided to the greatest extent, the calculation pressure and response time are decreased, and the timeliness and click rate prediction precision of advertisement putting are ensured.

The invention relates to the technical field of voice signal processing, and discloses a method and system for evaluating a spoken language. The method comprises the step of receiving a voice signal to be evaluated, the step of respectively obtaining voice fragments corresponding to basic voice units in the voice signal through at least two different voice recognition systems, the step of respectively extracting evaluating characteristics corresponding to different characteristics types from the voice fragments, the step of calculating original scores of the evaluating characteristics, the step of optimizing and fusing the original scores obtained based on the different voice recognition systems according to the characteristic types to obtain the comprehensive score of the evaluating characteristics, and the step of calculating the score of the voice signal according to the comprehensive score of the different evaluating characteristics. By means of the method and system for evaluating the spoken language, the accuracy of evaluating the spoken language can be improved, and abnormal grading can be reduced.

The invention discloses an automatic gain amplification circuit with an inverse exponential characteristic type digital control circuit, which is formed by a digital variable gain amplifier, a 2-bit flash analog-to-digital converter of a digital circuit and the inverse exponential characteristic type digital control circuit, wherein the digital variable gain amplifier is formed by cascading a plurality of digital variable gain amplifier stages; the 2-bit flash analog-to-digital converter comprises three comparator circuits, a coding circuit and a fixed reference voltage configuration circuit; and the inverse exponential characteristic type digital control circuit comprises a peak detector, a subtracter circuit, an integrator circuit and a decoding circuit. The inverse exponential characteristic type digital control circuit detects a digital signal output by the 2-bit flash analog-to-digital converter; the detected signal amplitude is compared with a reference value of a reference voltage by the subtracter circuit; and after a comparison result is integrated and decoded, a feedback control signal is output to regulate the gain of the variable gain amplifier PGA (Programmable Gain Amplifier). The automatic gain amplification circuit further comprises a switch for the control circuit, the switching between the inverse exponential characteristic type digital control circuit and an external control circuit can be implemented, and the automatic gain amplification circuit is particularly suitable for a radio frequency front-end circuit with the requirements on few off-chip components and compact structure.

The invention provides a method and system for automatically generating features of a machine learning sample. The method comprises the steps that (A) a user-specified data table is acquired, whereinone row of the data table corresponds to a data record, and one column of the data table corresponds to a field; (B) the feature type corresponding to each non-target value field in the data table isdeclared, wherein the feature type comprises a discrete feature and / or a continuous feature; (C) each non-target value field is processed into a unit feature according to the declared feature type; (D) feature combination is carried out based on the generated unit features to generate a combined feature; and (E) the features of the machine learning sample are acquired based on the generated unit features and the combined feature. According to the invention, the method and the system can automatically generate the features of the machine learning sample based on the data table; the use threshold of feature engineering is reduced; the usability of the feature engineering is improved; and the efficiency of feature engineering is improved.

In a SQUID magnetometer, high resolution, a high slew rate, and a high dynamic range are achieved without using expensive circuit components having a large number of processing bits and enabling a high speed processing operation. A digital FLL circuit using a double counter system is provided. This circuit utilizes two or more counters, for example, a change range counter in a digital FLL for carrying out a processing operation at a high speed and a reproducing counter in a control / measuring computer. In addition, in the present invention, hysteresis characteristics having a 1Φ0 positive margin is used. That is, a change of a state of a magnetic flux is counted by means of a counter. At the time of this change, control is made so as to track a different channel between cases in which a magnetic flux increases and decreases, thereby stabilizing the control.

The invention relates to a method for automatically adjusting voltage of electric arc of slope characteristic type pulse consumable electrode gas shielded welding, which mainly quantitatively adjusts the automatic adjustment intensity of the arc length and builds a slope characteristic type welding power supply control system through an arc length automatic adjusting model by an external characteristic slope algorithm of a welding power supply. The method takes the external characteristic slope as a criterion, takes the peak current time as a control quantity, and makes the voltage of the electric arc and the arc length automatically adjusted to a stable working point in the pulse consumable electrode gas shielded welding process. The method has the advantages of simpleness, effectiveness, adaptive parameter adjusting function and strong adaptability, and can be used for MIG welding, MAG welding and CO2 gas shielded welding.