403 results about "Single parameter" patented technology

Described is a technique for a backup and restoration of data in a network that includes a multi-lingual file system and a multi-lingual network file server. Multiple meta data files are associated with a single data file in the network. Provided are services for packaging the metadata as a single parameter of an application programming interface (API) for a particular data file being backed up or restored over a network. These techniques may be used in both full and incremental backups and restores of data over a network.

A system for fully integrated collection of business impacting data, analysis of that data and generation of both analysis-driven business decisions and analysis driven simulations of alternate candidate business actions has been devised and reduced to practice. This business operating system may be used predict the outcome of enacting candidate business decisions based upon past and current business data retrieved from both within the corporation and from a plurality of external sources pre-programmed into the system. Both single parameter set and multiple parameter set analyses are supported. Risk to value estimates of candidate decisions are also calculated.

A method and apparatus are implemented in software to control motor speed as a function of available power in a DC source—inverter—AC motor system, i.e. to perform maximum power tracking of motor speed. An inverter or motor drive converts DC power from a DC source, such as a solar panel, to AC power, to power the motor. The inverter or motor drive is controlled by software, implemented either by programmable features built directly into the inverter or drive or by a separate programmable device connected to the inverter or drive, to track motor power as a function of source power. The software-controlled inverter or drive sets motor speed as a function of source power by sensing only a single parameter, the DC source voltage. The software-controlled inverter or drive samples the source voltage at preset intervals, and changes the frequency of the AC output of the inverter or drive to match or track the available power so that the motor operates at or near its optimum for any source voltage.

Methods for analyzing retinal tomography maps to detect patterns of optic nerve diseases such as glaucoma, optic neuritis, anterior ischemic optic neuropathy are disclosed in this invention. The areas of mapping include the macula centered on the fovea, and the region centered on the optic nerve head. The retinal layers that are analyzed include the nerve fiber, ganglion cell, inner plexiform and inner nuclear layers and their combinations. The overall retinal thickness can also be analyzed. Pattern analysis are applied to the maps to create single parameter for diagnosis and progression analysis of glaucoma and optic neuropathy.

The invention discloses a psychological stress assessment method based on multi-physiological-parameter integration. The method includes: designing a reasonable stimulation program, acquiring four types of electrophysiological signals, namely electrocardiogram signals, electromyographic signals, pulse wave signals and electroencephalogram signals from people suffering psychological stress; extracting affective features of the four types of electrophysiological signals; subjecting the extracted features to feature selection by means of Relief algorithm, genetic algorithm optimization and the like; acquiring related integration functions on the basis of basic probability assignment mass. According to the method, multi-parameter signals are subjected to acquisition, preprocessed, feature selection and psychological stress affective recognition and are integrated; compared to single-parameter classified recognition or multi-parameter data-level or feature-level integration, the method allows data information to be more fully utilized and psychological stress emotions to be more accurately recognized.

A method of parameter adaptation is used to modify the parameters of a model to improve model performance. The model separately estimates the contribution of each model parameter to the prediction error. It achieves this by transforming to the time-scale plane the vectors of output sensitivities with respect to model parameters and then identifying the regions within the time-scale plane at which the dynamic effect of individual model parameters is dominant on the output. The method then attributes the prediction error in these regions to the deviation of a single parameter from its true value as the basis of estimating individual parametric errors. The proposed Signature Isolation Method (PARSIM) then uses these estimates to adapt individual model parameters independently of the others, implementing, in effect, concurrent adaptation of individual parameters by the Newton-Raphson method in the time-scale plane. The Signature Isolation Method has been found to have an adaptation precision comparable to that of the Gauss-Newton method for noise-free cases. However, it surpasses the Gauss-Newton method in precision when the output is contaminated with noise or when the measurements are generated by inadequate excitation.

Fiber optic grating sensor demodulation systems are described that offer high speed and multiplexing options for both single and multiple parameter fiber optic grating sensors. To attain very high speeds for single parameter fiber grating sensors ratio techniques are used that allow a series of sensors to be placed in a single fiber while retaining high speed capability. These methods can be extended to multiparameter fiber grating sensors. Optimization of speeds can be obtained by minimizing the number of spectral peaks that must be processed and it is shown that two or three spectral peak measurements may in specific multiparameter applications offer comparable or better performance than processing four spectral peaks. Combining the ratio methods with minimization of peak measurements allows very high speed measurement of such important environmental effects as transverse strain and pressure.

The invention provides a double-period dynamic configuration method for ratio between TDD (Time Division Duplex) uplink subframes and TDD downlink subframes, which is used for configuring a ratio between the time division duplex uplink subframes and the time division duplex downlink subframes of first communication equipment which supports an eIMTA function and second communication equipment which does not support the eIMTA function. The dynamic configuration method comprises the following steps of: determining a first configuration parameter for the ratio between the time division duplex uplink subframes and the time division duplex downlink subframes, which is to be applied to the first communication equipment; determining a corresponding second configuration parameter according to one or more history first configuration parameter used by the first communication equipment; and applying the first configuration parameter to the first communication equipment within a first reconfiguration period and applying the second configuration parameter to the second communication equipment within a second reconfiguration period. The invention further discloses a corresponding base station, a corresponding system and corresponding communication equipment. Through the adoption of a technical scheme of the invention, the different configuration parameters can be adopted for different communication equipments during hybrid networking of the communication equipments with different versions, so that performance degradation of partial communication equipments due to the use of single parameter is avoided.

The invention discloses an air conditioner and an intelligent temperature and humidity regulating method thereof, belongs to the field of air conditioners and temperature controlling methods thereof and aims at solving the problems of single parameter and the like of an existing temperature controlling method of the air conditioner. The intelligent temperature and humidity regulating method of the air conditioner includes that temperature and / or humidity of an environment is detected in real time by a controlling device of the air conditioner, the detected real-time temperature and / or humidity is subjected to comparison with a temperature and humidity reference range table prestored in the controlling device of the air conditioner, and when the environmental temperature and / or humidity is beyond the range of the temperature and humidity reference range table, the air conditioner starts to regulate the environmental temperature and / or humidity until the environmental temperature and / or humidity is within the range of the temperature and humidity reference range table. The air conditioner at least comprises the controlling device, a temperature probe and a humidity probe. The intelligent temperature and humidity regulating method and the air conditioner have the advantages of better user experience, more convenience in use, better achievement of intelligence by one key and wide application range.

A microscope control apparatus is used with a microscope apparatus attached with a microscope objective lens having an aberration correction lens. The microscope control apparatus includes a memory in which information on driving amounts of the aberration correction lens that are optimum for various observation conditions respectively, entry device for allowing an observer to enter a single parameter or multiple parameters for specifying an observation condition set upon observation, and calculation device for determining a driving amount of the aberration correction lens that is optimum for the observation condition specified by the parameter(s) based on the information.

The invention particularly relates to a design and setting method for an active disturbance rejection control system of a time delay system. According to the method, based on the active disturbance rejection technology, firstly, complex controlled objects are fit into a one-order inertial element plus dead time delay mathematic model, meanwhile, time delay comes down to the disturbance quantity, a time delay reduction linear extended state observer is applied to estimation of unknown total disturbance including the time delay, active compensation for the influences of the total disturbance on the system is achieved, the time delay system is restored into a system in an integrator tandem type in an ADRC standard, and then compensation for the time delay system is achieved; finally, a closed-loop transfer function of the system is deduced, a dead time delay link in a characteristic equation is eliminated, and the numerical relationship between an ADRC single-parameter setting formula with universality and adjustable parameters is correspondingly provided. The simulation result verifies that designed practical ADRC has good stability, rapidity, accuracy and disturbance rejection.

Methods and systems for building and using a parameter isolation model to isolate measurement signal information associated with a parameter of interest from measurement signal information associated with incidental model parameters are presented herein. The parameter isolation model is trained by mapping measurement signals associated with a first set of instances of a metrology target having known values of a plurality of incidental model parameters and known values of a parameter of interest to measurement signals associated with a second set of instances of the metrology target having nominal values of the plurality of incidental model parameters and the known values of the parameter of interest. The trained parameter isolation model receives raw measurement signals and isolates measurement signal information associated with a specific parameter of interest for model-based parameter estimation. The number of floating parameters of the measurement model is reduced, resulting in a significant reduction of computational effort.

Methods for analyzing retinal tomography maps to detect patterns of optic nerve diseases such as glaucoma, optic neuritis, anterior ischemic optic neuropathy are disclosed in this invention. The areas of mapping include the macula centered on the fovea, and the region centered on the optic nerve head. The retinal layers that are analyzed include the nerve fiber, ganglion cell, inner plexiform and inner nuclear layers and their combinations. The overall retinal thickness can also be analyzed. Pattern analysis are applied to the maps to create single parameter for diagnosis and progression analysis of glaucoma and optic neuropathy.

A method for data processing, comprising providing a sequence of image frames that is encoded by identifying intra and inter frames in the sequence and applying a variable block size motion compensation (VBSMC) procedure to the inter frames, thereby generating respective parameters representing the inter frames; selectively encrypting the block sizes, using an encryptor, without encrypting all of the parameters representing the inter frames; and outputting encoded data representing the sequence of the image frames and comprising the encrypted block sizes.

The invention discloses a residential building indoor environment monitoring and health grade evaluation Internet of Things system, and belongs to the fields of the residential building indoor environment detection technology and the information communication technology. The residential building indoor environment monitoring and health grade evaluation Internet of Things system is characterized in that indoor various-function room environment parameters are acquired in real time by utilizing data acquisition modules, and influence weights and health risk grades of the various indoor environment parameters on human health are comprehensively analyzed; and an expert opinion on improving of a corresponding environment condition and an expert strategy for improving the corresponding environment condition are given. An Internet of Things real-time data monitoring system is built at the same time, data can be timely transmitted to a user display terminal and a remote central service system, and the data can be taken as basic research data and a decision basis of a relevant government department. The residential building indoor environment monitoring and health grade evaluation Internet of Things system is advantageous in that the problem that the fact that the indoor environment is represented by a single parameter is unscientific is solved, real-time monitoring of the residential environment indoor comprehensive evaluation parameters and user mobile terminal contrast result synchronous searching can be achieved at the same time, and an suggestion for effective improvement of the environment and a measure for effectively improving the environment are obtained; and the residential building indoor environment monitoring and health grade evaluation Internet of Things system has the advantages of the wide application aspect and the high popularizing rate.

The invention discloses a nonlinear fuzzy detection method for operating safety of a power cable tunnel. The method comprises the following steps of: determining a project layer, a subproject layer and an index layer in a model, detecting the index layer and acquiring data; establishing a comment set; establishing a deterioration grade of each evaluation index and a membership function matrix of a corresponding comment set; determining weight of each level of evaluation indexes; sequentially calculating fuzzy evaluation matrixes of the index layer and the subproject layer by using an analytic hierarchy method until a final fuzzy evaluation result vector is obtained; and determining an evaluation result of an operating safety state of the power cable tunnel by using a maximum membership degree method. Single parameter early warning of the operating state of the cable tunnels and cables is realized, comprehensive on-line safety index evaluation and early warning are realized, technical support is provided for timely and effectively processing operating hidden dangers and failures of the cables, and after the project is finished, abnormal power failure can be reduced, and major disasters can be warned in advance; and an inspection workload of a worker is reduced. After the project is finished, the method can be popularized nationwide and has high economic and social benefits.

A system for heart performance characterization and abnormality detection includes an acquisition device for acquiring an electrophysiological signal representing heart beat cycles of a patient heart. A detector detects one or more parameters of the electrophysiological signal of parameter type comprising at least one of, (a) amplitude, (b) time duration, (c) peak frequency and (d) frequency bandwidth, of multiple different portions of a single heart beat cycle of the heart beat cycles selected in response to first predetermined data. The multiple different portions of the single heart beat cycle being selected from, a P wave portion, a QRS complex portion, an ST segment portion and a T wave portion in response to second predetermined data. A signal analyzer calculates a ratio of detected parameters of a single parameter type of the multiple different portions of the single heart beat cycle. An output processor generates data representing an alert message in response to a calculated ratio exceeding a predetermined threshold.

The invention belongs to the technical field of image processing and mode recognizing and relates to a fatigue driving detection method based on eye and mouth states. The method includes the steps of diver's video image acquisition, light compensation preprocessing, facial area detection, comprehensive fatigue judgment and fatigue alerting. The step of facial area detection includes eye detection and mouth detection; eye detection includes acquiring an eye area by means of a projection method, analyzing eye features, comparing the eye features to standard features, and performing k-means computation and eye fatigue judgment; mouth detection includes acquiring a mouth area by the mouth-map method, analyzing mouth features, comparing the mouth features to standard features, performing p-means computation and yawn judgement. According to the method, the eye feature parameter and the mouth feature parameter are combined for judgment; compared with the use of the single parameter, the method has higher rate and reliability of fatigue judgment; by the use of the method, traffic accidents caused by driver's fatigue driving can be greatly decreased; a new preventive measure is provided for ensuring life and property safety of drivers.

The invention relates to a portable impedance measurement instrument based on FPGA (field programmable gate array), belonging to the technical field of impedance measurement. The portable impedance measurement instrument based on the FPGA is characterized in that the impedance measurement instrument includes a microprocessor module, a sine signal generator module, a self-balancing bridge module, an automatic gain adjustment module, a phase sensitive demodulation module, a display module and a power supply module; the microprocessor module is connected with the sine signal generator module, the self-balancing bridge module, the automatic gain adjustment module and the phase sensitive demodulation module; the impedance measurement value is displayed by the display module; and the power supply module is used for supplying power to the circuit. The portable impedance measurement instrument has the advantages of simple measurement circuit, high integrity, high digital degree, small size and good portability, and is economic and practical, and can meet the requirement for impedance measurement in the common engineering field. The instrument can measure single parameters of impedance, capacitance and inductance or complex impedance parameters including resistance, capacitance and inductance, and can also achieve sweep frequency measurement.

The invention discloses a load prediction and condition constraint-based control method for an air conditioner cold source energy efficiency model. The control method comprises the following steps ofestablishing a cooling load prediction model; respectively establishing a water cooled host energy consumption model, a cooling tower energy consumption model, a chilled water pump energy consumptionmodel and a cooling water pump energy consumption model according to constraint conditions; establishing the central air conditioner cold source energy efficiency model according to the water cooled host energy consumption model, the cooling tower energy consumption model, the chilled water pump energy consumption model and the cooling water pump energy consumption model; and performing initialization assignment on the central air conditioner cold source energy efficiency model by the cooling load prediction model to enable the central air conditioner cold source energy efficiency model to perform optimum operating parameter setting on an central air conditioner. According to the embodiment of the invention, by changing control over an central air conditioner system into integral control over a construction cold energy demand model from single parameter control, and by analyzing energy efficiency conditions under different working conditions from the aspect of global energy efficiencyof a cold source, optimum operating parameter setting on the central air conditioner is realized, and therefore, energy conservation in a real sense is achieved.

The invention relates to an RBF-neural-network-based atmospheric pollutant concentration prediction method. The RBF-neural-network-based atmospheric pollutant concentration prediction method includesthe steps: dividing experimental data according to the actual situation of the predicted area, and pre-processing the atmospheric pollutant concentration data; using the MMOD improved K-means++ algorithm to solve the center of clustering, and calculating each kernel function width based on the variance; sampling the experimental data, wherein data subsets taking part in creation of RBF neural networks are IOB, and the remaining data that are not drawn are OOB data; evaluating learners to screen out the RBF neural network with the smallest generalization error, training an integrated RBFNN model; and by means of the weighted integrated RBFNN algorithm, based on weighted Euclidean distance, training single parameter through the center of clustering, the width and the weight to optimize RBFNN, and applying the single parameter to the integrated RBFNN to predict data. The RBF-neural-network-based atmospheric pollutant concentration prediction method is applied to atmospheric pollutant concentration prediction, and can greatly improve accuracy of atmospheric pollutant concentration prediction.

The invention belongs to the technical field of road traffic detection and particularly discloses an expressway road traffic state estimation method based on a dynamic Bayesian network; the method comprises the following steps: (1) extracting relevant parameters of the road traffic state as nodes; (2) determining an interrelationship among the nodes and establishing the dynamic Bayesian network; (3) carrying out a fuzzy classification on data of the observable nodes, analyzing the historical data to obtain a clustering center of each classification and determining a membership degree of the data of the observable data, belonging to each classification; 4) for a target node selected in the dynamic Bayesian network, acquiring a corresponding conditional probability and a transition probability and establishing each moment characteristic table of the selected target node; 5) inputting road traffic flow parameters of the current moment to the dynamic Bayesian network and triggering to reason a target of each moment to obtain a traffic state estimation result. According to the expressway road traffic state estimation method disclosed by the invention, the uncertainty in a single parameter estimation state is solved and simultaneously the relevance in the traffic state is considered, so that better effect and reliability when the road traffic state is estimated are achieved.

The present invention discloses a product quality control method based on integration learning. For prediction of product key quality indexes (yield) in different progresses in a production flow, themethod comprises the following steps of: (1) data analysis based on injection molding data; (2) feature engineering analysis and construction; (3) model design based on integration learning; (4) unbalance processing of data; and (5) multi-model fusion processing scheme. For recommendation of the optimal preset value of process parameters in the production process, the method comprises the following steps of: (6) whole process adjustable parameter recommendation; and (7) for un-adjustable parameters of a special process, recommendation of process adjustable parameters. The product quality control method is suitable for the processing unbalance data in the industrial data to break through a traditional product quality control single parameter analysis mode, and constructs and excavates internal feature relations between parameters through the feature engineering of the machine learning to discover the abnormality of the production process and improve the product quality control.

The invention discloses an adaptive detection method for a distance expanded object based on a variable-element generalized structure, belongs to the field of radar signal processing. Aimed at solving the problem that a covariance matrix estimation method and an adaptive distance expansion detector are hard to adapt to a transitional clutter environment, clutter non-Gaussian characteristic information is utilized reasonably, a unified covariance matrix fusion estimation framework is constructed, an adaptive detector of the distance expanded object is constructed in a product fusion form on the basis of general characteristics of detection statistics of present optimal distance expanded objects in the specific clutter environment, a single parameter is utilized to realize design of the detector for the distance expanded object in the transitional clutter environment as well as synchronous control of the corresponding clutter covariance matrix estimation method, the detector structure matches the corresponding clutter covariance matrix estimation method, parameters are set in a concise manner, the detection performance of a broadband radar in the complex clutter environment is improved effectively, and the popularization and application values are high.

A vehicle control system includes a control portion configured to determine a single parameter based on a running condition of a vehicle, and determine control amounts for a plurality of actuators provided in the vehicle based on the parameter. A relation of the control amount for each of the plurality of actuators to the parameter is predetermined. The control portion is configured to, when the parameter is determined, determine the control amounts for the respective actuators based on the parameter, and control the actuators based on the determined control amounts.

The invention relates to an analysis and optimization method for the steady-state performance of a variable-cycle engine. The method includes the first step of checking an engine performance calculation program, the second step of carrying out single-parameter adjustment influence analysis, the third step of selecting independent variables, an independent variable range and responsive variables, the fourth step of selecting an experiment design method and a sample scheme, the fifth step of calculating the sample scheme, the sixth step of establishing an approximation model, the seventh step of establishing an optimization equation set and solving the optimization equation set, and the eighth step of carrying out engine characteristic analysis under multi-parameter coupling influences. By means of the method, more comprehensive influencing characteristics of adjustable component parameters on the optimization objective of the steady-state performance of the engine can be easily and visually obtained with a small scheme calculation amount according to a scientific data analysis method, the optimal adjustable component parameter matching scheme can be conveniently and rapidly obtained according to the optimization objective, and thus the steady-state performance of the engine is analyzed and optimized. The method has the advantages of being high in precision, easy to implement and the like.

A coverage analysis system for network optimization of mobile communication system, includes: a data import and export module; and individual analysis module, for determining coverage problem regions and coverage problem plots, call problem regions and call problem plots, and collecting the network configuration characteristic parameters; a comprehensive diagnostic analysis module, for comprehensively analyzing the information and parameters contained in the route measured data and the call testing data to determine the association correlation of the coverage problem regions and the call problem regions, and processing correlation andanalysis to determine the coverage and call associated problem regions and problem plots, so as to evaluate the coverage quality , call quality and network performance of the entire mobile communications network from different point. The present invention also provides a corresponding method. The present invention overcomes the problem in the existing technology that it can only analyze based on a single problem plot and a single parameter, and achieves the technical effects that it can carry out the overallanalysis analyze from the entire point of network, thus having a unified data management and strong data compatibility.

The invention provides a three-parameter feature fusion gesture recognition method based on a FMCW (frequency modulated continuous wave) radar. Firstly, the IF signals of different gestures are acquired by radar, from which the angle parameters, range parameters and Doppler frequency shift parameters are obtained, and the corresponding data sets are constructed. Secondly, the data sets of angle, range and Doppler frequency shift are trained in convolutional neural network, and the eigenvalues are obtained and fused. Finally, the fused eigenvalues are sent into the classifier to get the gestureclass. The invention innovatively proposes a fusion method of multiple parameters in a convolution neural network, solves the problem that the use condition of the traditional recognition algorithm is limited, and the classification effect of the final gesture is better than that of a single parameter.

Fiber Bragg gratings (FBGs) are particular suitable for measuring strain. However, a single parameter measurement is difficult to implement, since cross-sensitivity to temperature compels the use of an additional temperature reference, e.g. a strain-inactive FBG. The development of a passive athermal fiber Bragg grating strain gage is thus of particular interest since it renders optional the measurement of temperature, benefiting large scale system design and performance. In view of this need, a package for fiber Bragg gratings that enables strain measurements to be performed while canceling temperature sensitivity is disclosed. The proposed design is based on a structure composed of two parts, which can be made of the same material, having a defined length ratio that allows the adjustment of the temperature sensitivity to zero, providing athermal operation of the strain gage. Moreover, the disclosed passive athermal scheme is adjustable to further compensate for structural thermal expansion, enabling the load-induced strain component to be decoupled from the temperature-induced strain component.