280 results about "Function type" patented technology

The method comprises: reading out the pre-configured test solution; according to the function type in said test solution, calling the relevant functional test script; said functional test script calls a browser to open the relevant webpage window of the Web application system under test, and records the identifier of the webpage window; said functional test script calls the browser interface to input the data and operation of current test solution into said webpage window to get test result.

A method and system for developing data integration applications with reusable semantic types to represent and process application data. Methods include creating schemas to describe external data, creating semantic types to describe internal data, mapping schemas to semantic types, developing dataflows that configure input and output operations using schemas, mappings, and semantic types and all other transformation operations and functions based solely on semantic types, and executing dataflows defined in this manner.

In a server system, functions of blade servers can be visually recognized at a glance. A change in load due to a failure can be detected to modify the system configuration by changing functions of blade servers. The server system includes a blade system including servers having different function types, the servers being installed in one or more stages in one enclosure, and a managing server for managing the blade system. The managing server includes a first managing section for classifying the servers into groups, a second managing section for managing a state of arrangement of the servers in the enclosure, and an arrangement changing section for changing functions of the servers discretely and for changing arrangement of the servers in the enclosure by replacing functions of the servers. The arrangement changing section arranges the servers in the enclosure on a function basis of the servers.

One or more machine code entities such as functions are created which represent solutions to a problem and are directly executable by a computer. The programs are created and altered by a program in a higher level language such as "C" which is not directly executable, but requires translation into executable machine code through compilation, interpretation, translation, etc. The entities are initially created as an integer array that can be altered by the program as data, and are executed by the program by recasting a pointer to the array as a function type. The entities are evaluated by executing them with training data as inputs, and calculating fitnesses based on a predetermined criterion. The entities are then altered based on their fitnesses using a machine learning algorithm by recasting the pointer to the array as a data (e.g. integer) type. This process is iteratively repeated until an end criterion is reached. The entities evolve in such a manner as to improve their fitness, and one entity is ultimately produced which represents an optimal solution to the problem. Each entity includes a plurality of directly executable machine code instructions, a header, a footer, and a return instruction. The instructions include branch instructions which enable subroutines, leaf functions, external function calls, recursion, and loops. The system can be implemented on an integrated circuit chip, with the entities stored in high speed memory in a central processing unit.

The invention relates to a method for setting accidence diagnose and accidence prediction, which comprises a real-time data interface and a processing module. It provides many kinds of data interfaces to collect and treat data. Wherein, the accidence diagnose and accident prediction module can real-time detect the state of device, and diagnose accidence to alarm and give treating advice; the process detecting, accidence diagnose, accidence analysis and prediction are based on real-time data, that used in process control system; it uses the real-time and history database system modules to provide to the data service of alarm processing module, and provide the quick search of real-time and history data via function type; the alarm unit comprises an alarm operation function treating unit, an alarm container and an alarm manage unit. The invention can integrate the process detection, accidence diagnose, accidence analysis prediction and on-line operation instruction.

The present invention provides a control device that controls home electrical appliances via a communication line by using function codes which are set without being specialized for specific home electrical appliances. In particular, the present invention provides a home electrical appliance control device that controls a home electrical appliance connected via a communication line, where the device includes: a memory section for storing a function table for mapping function identifiers, which identify function types allocated with the focus on the function itself to functions with which the home electrical appliance is equipped, with attributes of the functions, and a control section for controlling the home electrical appliance via the communication line based on the function table.

One or more machine code entities such as functions are created which represent solutions to a problem and are directly executable by a computer. The programs are created and altered by a program in a higher level language such as "C" which is not directly executable, but requires translation into executable machine code through compilation, interpretation, translation, etc. The entities are initially created as an integer array that can be altered by the program as data, and are executed by the program by recasting a pointer to the array as a function type. The entities are evaluated by executing them with training data as inputs, and calculating fitnesses based on a predetermined criterion. The entities are then altered based on their fitnesses using a machine learning algorithm by recasting the pointer to the array as a data (e.g. integer) type. This process is iteratively repeated until an end criterion is reached. The entities evolve in such a manner as to improve their fitness, and one entity is ultimately produced which represents an optimal solution to the problem. Each entity includes a plurality of directly executable machine code instructions, a header, a footer, and a return instruction. The alteration process is controlled such that only valid instructions are produced. The headers, footers and return instructions are protected from alteration. The system can be implemented on an integrated circuit chip, with the entities stored in high speed memory in a central processing unit.

The invention provides a relevance vector machine-based multi-class data classifying method, which mainly solves the problem that the traditional multi-class data classifying method cannot integrally solve classifying face parameters and needs proximate calculation. The relevance vector machine-based multi-class data classifying method comprises a realizing process comprising the following steps of: partitioning a plurality of multi-class data sets and carrying out a normalizing pretreatment; determining a kernel function type and kernel parameters; setting basic parameters; calculating the classifying face parameters; calculating lower bounds of logarithms and solving variant values of the lower bounds of the logarithms and adding 1 to an iterative number; if the variant values of the lower bounds of the logarithms are converged or the iterative number reaches iterating times, finishing updating the classifying face parameters, and otherwise, continuing to updating; and obtaining a prediction probability matrix according to the updated classifying face parameters, wherein column numbers corresponding to a maximum value of each row of the matrix compose classifying classes for testing the data sets, and samples which have the prediction probability less than a false-alarm probability and the detection probability corresponding to a false-alarm probability value set in a curve are rejected. The relevance vector machine-based multi-class data classifying method has the advantages of obtaining classification which is comparable to that of an SVM (Support Vector Machine) by using less relevant vectors and rejecting performance and can be used for target recognition.

Method for reducing the fogging effect in an electron beam lithography system wherein the exposure is controlled in order to obtain resulting pattern after processing which are conform to design data. A model for the fogging effect is fitted by individually changing at least the basic input parameters of the control function, the function type is chosen in accordance to the Kernel type used in the proximity corrector. The proximity effect is considered as well and an optimised set of parameters is obtained in order to gain a common control function for the proximity and fogging effect. The pattern writing with an e-beam lithographic system is controlled by the single combined proximity effect control function and the fogging effect control function in only one data-processing step using the same algorithms as are implemented in a standard proximity corrector.

A system and method is presented for diagnosing problems in a sensor, a vehicle computer and a vehicle sensor wiring harness. The diagnostic system comprises a sensor simulator configured to be selectively coupled to the vehicle computer via a wiring harness during a diagnostic mode, and to eliminate and simulate a known good sensor to the vehicle computer by way of the vehicle sensor wiring harness directly connected therebetween. The system includes an external computer adapted to selectively couple the sensor simulator to the vehicle computer, and a user keypad and memory to receive and store user commands of a selected manufacturer's make, model, year of vehicle, and the function type of the selected sensor, and to enable the user to select or adjust a typical operational value comprising one or more of a voltage, current or resistance operational range values of the selected sensor.

The present invention belongs to the manufacture technology of composite material, which relates to predefinite form agent of toughening function type RTM textile powder and a preparing method thereof. The predefinite form agent of toughening function type RTM textile powder is formed by mixing a component A and a component B. The component A is high-performance thermoplastic polymer powder which can not be hardened and conglutinated, and meanwhile, the high-performance thermoplastic polymer powder is mainly distributed among the composite material after the composite material is formed to improve the shock resistant strength of the composite material. The component B is resin component with a proper softening point, and the softening point of the resincomponent is between 40 DEG C to 100 DEG C. The high-performance thermoplastic polymer powder occupies to 5% to 80 % of the total amount of the predefinite form agent, and the rest is the component A. The preparing method comprises the following steps of component A preparation, component B preparation and mixing. The predefinite form agent of toughening function type RTM textile powder can be avoided to be hardened under a condition of storing at room temperature for a long time, the predefinite form effect of textile is improved, and the compression performance after shocking of predefinite form textile RTM composite material, but the heat resistance and the mechanical property of the composite material are not affected. The predefinite form agent of toughening function type RTM textile powder comprises double-horse resin type, epoxy resin type and isocyanate resin type definite form agents.

Converting from a database system to another database system. The conversion process including translating a set of queries for the first database to be used in the second database by determining the query types of the parent and child queries and generating the translated queries according to the type of the query. The type of the query judged as the stored-procedure or the dummy type, irrespective of the existence of a parent query, the function type query after conversion other than the same stored-procedure type query after conversion of the function are generated in all cases. As a result problem is not occurred even when there is a parent.

The invention aims to solve the problems in the existing traffic signboard recognition method that the recognition target falls into a single group and the speed in doing so is slow. The invention, out of this concept, provides a fast traffic signboard recognition method based on convolution neural network, referred to as FTSR-CNN in abbreviation. This method comprises: using the convolution kernel sliding filter extracted characteristics; obtaining the loss of the network in the forward learning process, and ensuring the accuracy of the network model to the recognition of multiple categories of signboards; optimizing the network performances through the adjustment of the parameters, the activation of the function types and the reduction of dimensions for better accuracy and timeliness eventually; and at the same time, in order to make the samples more diverse, conducting data adding and expanding to the samples in the data set based on affine transformation. The recognition rates of the FTSR-CNN for two data set tests of the German traffic signboard data set GTSRB and the Tsinghua-Tencent 100K are recorded as 95.74% and 96.67% respectively. The results indicate that the recognition speed is increased on the same recognition accuracy level through the modification of a previous model network and the start up of different training strategies by the FTSR-CNN.

Optical Fourier transform is executed over a wide time range. A quadratic function type optical pulse generator (7) generates a control light pulse of a shape expressed by a quadratic function or a parabola according to a clock signal based on a signal light pulse from an optical coupler (1). The signal light pulse inputted is multiplexed by a multiplexer (9) with the control light pulse optically delayed by an optical delay element (8) so that the timing is matched with the signal light pulse, and introduced into an optical Kerr medium (10). In the optical Kerr medium (10), the signal light pulse inputted by the mutual phase modulation between the signal light pulse and the control light pulse is subjected to a linear phase modulation (frequency chirp) over the entire pulse or a wide time range. After that, the signal light pulse isolated by an optical filter (11) is introduced into the dispersion medium (12) having a group velocity dispersion (secondary dispersion), thereby converting the time waveform of the inputted signal light pulse into the shape of the frequency spectrum.

The invention provides a traditional Chinese medicine contrast medium adjuvant used for B ultrasonic, which comprises the following materials in part by weight: 10-20 parts of bighead atractylodes rhizome, 10-20 parts of poria cocos, 10-20 parts of turmeric, 10-20 parts of tangerine peel, 10-20 parts of cortex magnoliae officinalis, 10-20 parts of radix aucklandiae, 10-20 parts of Rhizoma atractylodis, 10-20 parts of cuttlebone, 10-20 parts of calcined oyster shell, 10-20 parts of Chinese yam, 10-20 parts of charred triplet, 10-20 parts of myristica fragrans, 10-20 parts of gizzard pepsin, 10-20 parts of rhizome cyperi, 10-20 parts of codonopsis pilosula, 10-20 parts of combined spicebush root, 10-20 parts of eclipta, 10-20 parts of jasmine, 10-20 parts of baical skullcap root and 10-20 parts of field pennycress. The traditional Chinese medicine contrast medium adjuvant used for B ultrasonic provided by the invention not only can adapt to stomach hyperfunction type, but also can adapt to decreased stomach function type, and also can be applied to the mixed type of various flatulence and mucinosis, check time is short, imaging rate is high, and preparation process is simple and practical. The contrast medium adjuvant has no obvious toxic side effect and has prospect on further development research.

A system that passes algorithms or functions between dependency nodes of a dependency graph in a graphic creation process system using a pointer or by passing a self-evaluating data structure. An evaluation process associated with the graph includes an ability to distinguish between passed parameters based on type where one of the types allowed is a function type and types are identified dynamically as the dependency graph is executed. The node receiving the algorithm executes the received algorithm along with it's own algorithm avoiding the necessity of traversing the graph multiple times when a data series is executed. The system also provides a mapping that allows parameters of the function to be reordered to match the source and destination function requirements. Default values allow evaluation even when less than all parameters associated with the function are passed. Mapping flags allow passed parameters to be ignored.

The invention provides a city hot spot identification method based on mobile signaling data. The method comprises the following steps: (1) identifying a residing point according to residing duration of a user, and calculating contribution degree of a permanently residing user to a hot spot area; (2) from the number of residing people, judging an active honeycomb according to the value of the number of residing people; (3) performing similarity measurement for all the identified active honeycombs, and clustering based on a density algorithm to mine the hot spot areas of a city; (4) obtaining POIs data of each hot spot area; (5) performing theme setting for the hot spot areas according to the type of the POIs contained in each hot spot area. In the method provided by the invention, the existing mobile network information is used fully, residing point judgment, a permanently residing user attenuation factor and others are introduced for identifying distribution of the city hot spots and calibrating function types thereof, and a certain reference value is provided for going out, traveling and others of people.

The invention relates to an elderly cognitive function classification method based on a random forest and belongs to the technical field of biomedicine. The method disclosed by the invention comprises the following steps: dividing the elderly cognitive function into three types by adopting MMSE scale scores and education levels; extracting a key cognitive domain influencing elderly cognitive function category classification by utilizing a cognitive function score relative ratio calculation method and a Pearson linearly dependent coefficient calculation method; establishing a random forest regression model, calculating attribute significance scores of non-scale attributes, and extracting external related attributes influencing the elderly cognitive function category classification; finally, equalizing the sample set based on the extracted key cognitive domain and external related attributes by adopting an SMOTE up-sampling method, and establishing an elderly cognitive function classification model by utilizing the random forest method. Compared with a scale classification method, the method provided by the invention has the advantages that the adopted attributes are few and easy to collect, and the method has high convenience; compared with other machine learning algorithms, subdivision of the elderly cognitive function types is realized, and research of a method for performing targeted intervention on the elderly cognitive functions is facilitated.