54 results about "Intrinsic function" patented technology

A technique is disclosed for executing a compiled parallel application on a general purpose processor. The compiled parallel application comprises parallel thread execution code, which includes single-instruction multiple-data (SIMD) constructs, as well as references to intrinsic functions conventionally available in a graphics processing unit. The parallel thread execution code is transformed into an intermediate representation, which includes vector instruction constructs. The SIMD constructs are mapped to vector instructions available within the intermediate representation. Intrinsic functions are mapped to corresponding emulated runtime implementations. The technique advantageously enables parallel applications compiled for execution on a graphics processing unit to be executed on a general purpose central processing unit configured to support vector instructions.

The invention discloses a structural damage recognition method based on a Bayesian model. The method comprises the steps of firstly, using an empirical mode decomposition method to decompose obtainedsingle-point structure response through observation to obtain a time-varying intrinsic mode function to construct a likelihood function of the Bayesian model, using the likelihood function of the Bayesian model of the time-varying intrinsic function based on the single-point system structure response for an update method of the Bayesian model, and using a gradient Markov chain Monte Carlo algorithm in the design of the Bayesian model update method; direct sampling from model posterior probability distribution in which sampling is difficult to conduct is avoided, sampling is conducted in a series of simpler intermediate probability distribution which converges to the posterior probability distribution, through the method, an intermediate probability density function can be automatically selected, normalized parameters in a posterior probability distribution formula of model parameters are directly obtained, and the calculation efficiency is greatly improved.

A simulation model conversion method based on a distributed interactive simulation platform, includes the steps: (1)determining the time management mechanism used in the simulation model conversion process to make the federal member of the simulation model unitedly order the insulated clock of the distributed interactive simulation platform, executing the simulation step length propulsion of the simulation model according to the simulation clock of the distributed interactive simulation platform; (2)dividing the intrinsic function of the simulation model to be converted into two parts: one part being a state transition function, the other part being an event handling function; (3) according to the state transition function and the event handling function, determining the model state parameters of the simulation model to be converted ordered and issued for the distributed interactive simulation platform and the special event ordered and issued for the distributed interactive simulation platform, forming the interface describing file; (4) according to the interface describing file, generating the object class library and the interactive class library for the conversion of the model to be converted; (5) according to the generated object class library and interactive class library, reforming the model to be converted and completing the conversion of the simulation model.

A layout of a semiconductor circuit is analyzed to calculate layout-dependant parameters that can include a mobility shift and a threshold voltage shift. Layout-dependant effects that affect the layout dependant parameters may include stress effects, rapid thermal anneal (RTA) effects, and lithographic effects. Intrinsic functions that do not reflect the layout-dependant effects are calculated, followed by calculation of scaling modifiers based on the layout-dependant parameters. A model output function that reflects the layout-dependant effects is obtained by multiplication of each of the intrinsic functions with a corresponding scaling parameter.

A program development apparatus includes a storage device configured to store an operation definition defining a program description in a source program subjected to be optimized and a complex intrinsic function including an inline clause describing statements after the optimization. An analyzer is configured to perform a syntax analysis of the complex intrinsic function by reading the complex intrinsic function out of the storage device, so as to detect the operation definition and the inline clause. A code generator is configured to generate an object code from the source program by optimizing a program description corresponding to the operation definition in the source program into the statements in the inline clause.

The invention discloses an intrinsic function recognition method based on a sub-graph isomorphism matching algorithm in decompilation, and belongs to the technical field of decompilation. According to the method, an intrinsic function template library is established, sub-graph isomorphism matching is conducted on intrinsic function templates and target assembling files generated through decompilation on the basis of a control flow diagram, and intrinsic functions which are subjected to compiler optimization and inline expansion in target programs of the target assembling files are positioned. According to the intrinsic function recognition method, inline intrinsic functions in the decomplation process can be recognized automatically, meanwhile, the templates and prototypes of the intrinsic functions are analyzed, the function names, returned values, returned value types and function parameters of the intrinsic functions are recovered, and thus the purpose of promoting the semantics of the inline intrinsic functions is achieved. More type information is provided for type analysis in decompilation through the promoted inline intrinsic functions, the complexity of data flow analysis and control flow analysis is lowered, the level of abstraction of intermediate codes is improved, and the readability of decompilation results is enhanced.

The invention provides a single channel chaotic signal blind source separation method, and belongs to the technical field of electronic information. The separation method is characterized in that modules used in the method comprise an ensemble empirical mode decomposition module, a correlation analysis module, a principal component analysis module and an independent component analysis module. The separation method comprises the steps that single channel signals formed by mixing multichannel chaotic signals are decomposed to mutichannel intrinsic mode function components through the empirical mode decomposition module; first time dimensionality reduction is performed on pivot elements of the multichannel intrinsic function components by using correlation analysis; then second time dimensionality reduction is performed on the pivot elements of the multichannel intrinsic function components by using a main component analysis method; finally blind source separation of the mixture chaotic signals is completed by using independent component analysis technics, and source signals are restored. The separation method has the advantages that the number of transmission channels can be effectively decreased, the purposes of reducing the complexity of hardware and saving equipment cost are achieved, and the source signals can be restored quickly and effectively.

A system performs the power supply control of a plurality of information processing apparatuses at a low cost without relation to the intrinsic function of the information processing apparatus and the existence of a network facility. The power supply control apparatus of the present invention can be connected to at least one information processing apparatus. The power supply control apparatus comprises a power supply circuit that supplies electrical power to the information processing apparatus, a network connecting unit that connects a network with an administration apparatus for detecting a failure in operating conditions of the information processing apparatus, and a power supply control unit that controls power supply of the supply circuit on the basis of a power supply on/off instruction received from the administration apparatus via the network connecting unit.

The invention discloses a food processor with a post-fermentation function and a preparation method of fermentation raw pulp. There are three types of food processor which are different in the mounting modes of the motor, namely an inhead type, an underneath type and side-mounted type, wherein a control procedure for preparing the fermentation raw pulp is arranged on a control circuit board of the food processor with the post-fermentation function. The preparation method of the fermentation raw pulp comprises a step of fermenting food materials, water and edible zymophyte by using the intrinsic function of the food processor with the post-fermentation function to prepare the fermentation raw pulp; the whole process is free of artificial operation and the infectious microbe can be naturally killed in the preparation process, so that the infectious microbe pollution is avoided; in addition, viscid threads of natto are thoroughly stirred and mixed in natto raw pulp in the process of preparing the natto raw pulp; the overall nutrition of the natto is retained; the natto raw pulp is attractive in appearance, good in taste, rich in nutrition and suitable for domestic ordinary consumers; meanwhile, the operation process is simple, convenient, efficient and safe.

The embodiment of the invention relates to the field of intelligent devices, and discloses a mobile terminal. In the invention, the mobile terminal comprises a screen module and a shell module; the screen module is in a sliding connection with the shell module; the shell module comprises a function component region; the screen module is used for covering the function component region or exposing the function component region through relative sliding with the shell module; and the function component region is used for providing intrinsic functions of the function component region for users. Thus, when the functions of the function component region are used, the screen module can be slid to expose the function component region, when only the screen is used, the screen module is slid to coverthe function component region, use of the screen and use of the function component region cannot be in conflict, and better use experience is provided for the users.

The present invention discloses an electric device with a wireless communication module which receives weather information through a pager network, calculates well-being indexes from the weather information, and provides the well-being indexes to the user in a real time. The electric device with the wireless communication module includes a pager receiving module for receiving weather information signals through a pager network, and demodulating weather information from the weather information signals, a display means for displaying the weather information or well-being indexes relating to the weather information, a storing means for storing well-being index calculation data for calculating the well-being indexes from the weather information, and a control means for performing an intrinsic function of the electric device, receiving the weather information from the pager receiving module, reading the well-being index calculation data, calculating the well-being indexes according to the well-being index calculation data, and displaying at least one of the weather information and the well-being indexes on the display means.

The invention provides a method for generating a mask pattern model and a method for optimizing a mask pattern. The method for generating the mask pattern model comprises the following steps: S11, calculating an intrinsic function group under a set photoetching process condition, wherein the intrinsic function group comprises n intrinsic functions; s12, obtaining an imaging signal value set at each defined position of each test pattern, wherein the imaging signal value set comprises n imaging signal values, and each imaging signal value is calculated based on the convolution value of the intrinsic function and the optical transmission function in the intrinsic function group; S13, taking the imaging signal value set at each defined position of each test pattern as the input of a neural network model; S14, calculating a continuous tone mask pattern of each test pattern, and taking the continuous tone mask pattern as an output training target of the neural network model; S15, training parameters of the neural network model; S16, taking the trained neural network model as a mask pattern model. According to the method provided by the invention, an optimal mask pattern can be obtained.

The invention discloses an ultra-short-term wind power combination prediction method based on a support vector machine, and the method comprises the steps: firstly carrying out the linear interpolation replacement of to-be-processed wind power historical data according to the data of an adjacent time period, and carrying out the normalization of the preprocessed data; secondly, decomposing the processed wind power data into an eigenfunction sequence and a residual error sequence by using empirical mode decomposition; secondly, establishing a quantum particle swarm-support vector machine model for the eigenfunction sequence and the residual sequence obtained by decomposition, and performing training optimization to obtain a predicted value of each sequence; and finally, superposing the prediction values of the sequences to obtain a final wind power prediction value, and carrying out error evaluation analysis. Compared with a support vector machine direct prediction result or a result without data feature decomposition, the prediction result of the method is improved, and meanwhile the situation that local errors are too large does not occur. Compared with an existing wind power prediction scheme, the method is higher in robustness, higher in calculation speed, less in data requirement and better in prediction effectThe invention discloses an ultra-short-term wind power combination prediction method based on a support vector machine, and the method comprises the steps: carrying out the linear interpolation replacement of to-be-processed wind power historical data according to the data of an adjacent time period, and carrying out the normalization of the preprocessed data; secondly, decomposing the processed wind power data into a cost characteristic function sequence and a residual sequence by utilizing empirical mode decomposition; secondly, establishing a quantum particle swarm-residual sequence for the intrinsic function sequence and the residual sequence obtained by decomposition; carrying out training optimization on the support vector machine model to obtain a predicted value of each sequence; and finally, superposing the predicted values of the sequences to obtain a final wind power predicted value, and carrying out error evaluation analysis. Compared with a result of direct prediction of a support vector machine or no data feature decomposition, the prediction result of the method is improved, and meanwhile, the situation of overlarge local error does not occur. Compared with an existing wind power prediction scheme, the method is higher in robustness, higher in calculation speed, less in data demand and better in prediction effect.

The invention discloses a carbon emission price combination prediction method. The method includes the steps that 1, an original carbon emission price sequence is decomposed into a series of intrinsic function components through a variation mode decomposition algorithm; 2, an output variable is given, the input variable of each IMF component is determined through statistical tools comprising a partial autocorrelation function and a corresponding partial autocorrelation diagram thereof; 3, each IMF component is predicted through a Spiking neural network; 4, prediction results of all the IMF components are superimposed to obtain a predicted value corresponding to an original carbon emission price. By means of the method, prediction precision is effectively improved, and carbon emission price prediction can be well achieved.

The invention relates to the technical field of air-source heat pumps, in particular to an air-source heat pump drying room. The air-source heat pump drying room comprises a room body and is characterized in that the room body is internally provided with a drying chamber, an air passage circulation cavity is formed between the drying chamber and an inner cavity of the room body, and an air path switching unit is arranged in the air passage circulation cavity between an upper drying plate of the drying chamber and an upper plate of the room body. A fluorine system condenser in the drying room is separated from an evaporator, the condenser portion is a heating portion, and the evaporator portion is an air energy conversion and condensation and dehumidification portion. Air energy conversion and condensation and dehumidification functions are completed through air path switching by taking the advantage of intrinsic functions of the evaporator, and a current mode of adopting a double-evaporator or double-condenser mechanism for completing an internal and external dual-circulation dewatering process of the air-source heat pump drying room is changed. The drying room only adopts one normal fluorine system device to complete the internal and external dual-circulation dewatering process of the air-source heat pump drying room by air path switching, thereby having advantages of convenience in use, economical, energy efficient, completion of dehumidification and heating through air path switching, and the like.

A “kill” intrinsic that may be used in programs for designating specific data objects as having been “killed” by a preceding action is provided. The concept of a data object being “killed” is that the compiler is informed that no operations (e.g., loads and stores) on that data object, or its aliases, can be moved across the point in the program flow where the data object is designated as having been “killed.” The “kill” intrinsic limits the reordering capability of an optimization scheduler of a compiler with regard to operations performed on “killed” data objects. The “kill” intrinsic may be used with DMA operations. Data objects being DMA'ed from a local store of a processor may be “killed” through use of the “kill” intrinsic prior to submitting the DMA request. Data objects being DMA'ed to the local store of the processor may be “killed” after verifying the transfer completes.

The present invention provides a power cutoff device automatically operated upon the occurrence of a spark on an electric wire. The power cutoff device of the present invention automatically cuts off power supply to an earth leakage breaker or an electronic switch according to a control signal transmitted by detecting an electromagnetic wave due to an electric spark generated on an electric wire by an abnormal state such as a connection failure of an electrical device, thus preventing a disaster such as an electrical fire caused by the electric spark (flame). According to the present invention, since the power cutoff device provides an intrinsic function of the earth leakage breaker that operates in a state of an overload or electric leakage and the earth leakage breaker is operated by detecting the electric spark generated on the electric wire, it is possible to effectively prevent a disaster such as an electrical fire caused by the electric spark.

The invention discloses a method for adjusting an influence matrix of accurate matching of seismic waves and a target response spectrum. The method comprises introducing an intrinsic function of a six-order differential equation to decompose initial seismic waves; obtaining initial amplitude coefficients in one-to-one correspondence with the intrinsic functions; in each time of iterative computation, calculating the response spectrum of the seismic wave reconstructed by the intrinsic function by using the Duhamel integral; calculating the contribution value of each intrinsic function to the reaction spectrum at each calculation frequency. The method has the advantages that the contribution of each intrinsic function to the calculation of the reaction spectrum can be adjusted by adjusting the amplitude coefficient of the intrinsic function, so that the calculation of the reaction spectrum is uniformly and consistently close to the standard reaction spectrum in each iteration calculation, and the purpose of matching the calculation of the reaction spectrum with the target design reaction spectrum is finally achieved. According to the method, the iteration process is monotonous and convergent, so that the time-history dynamic response analysis result of the important engineering structure has high precision and reliability, and the discreteness and the time consumption are remarkably reduced.

The invention provides methods for identifying brain cells that determine and can evoke subjective states that do not contain smaller constituents, by establishing a correspondence between intrinsic function of a cell type with its hierarchy of constitutively-expressed proteins. The hierarchy level of a dysfunctional protein is of diagnostic value and is an effective target for therapeutic modification.

The invention discloses an improved influence matrix method for high-low frequency band alternation and target spectrum matching, which comprises the following steps: all intrinsic functions are selected in a low frequency band and intrinsic functions of which the intrinsic frequencies are in one-to-one correspondence with frequency calculation points of a target spectrum in a high frequency bandas a group of primary functions to decompose seismic waves, so that the dimension of an influence matrix is greatly reduced; the influence of different frequency components on each other and the difference of contribution values to the target spectrum are considered, and the reaction spectrum is gradually close to the target design spectrum within the full frequency range by alternately adjustingthe amplitude coefficients of the full-band and high-band intrinsic functions, so that a very good matching effect can be achieved within the key attention frequency range of a project. The method overcomes the defects that in an existing response spectrum matching influence matrix method, the influence matrix dimension is large in the iteration process, the calculation efficiency is low, and different requirements of high frequency bands and low frequency bands cannot be met at the same time. Therefore, the dynamic time-history response analysis efficiency of the important engineering structure is greatly improved, and the precision and reliability are high.

A time domain signal analysis method is provided. The signal analysis method includes the following steps. A signal to be analyzed is received. The signal to be analyzed is iteratively sifted by using Empirical Mode Decomposition (EMD) to extract at least one intrinsic function (IMF). A normalized Hilbert transform is performed on the IMF. The transformed IMF includes phase information. The transformed IMF is processed by means of phase processing to obtain the processed IMF including angular frequency information. The foregoing signal analysis method could be utilized in an ultrasound imaging system to identify image information of ultrasound images.