140results about How to "Overcome subjectivity" patented technology

The invention discloses a motor function rehabilitation monitoring system based on a wireless body area network. The system comprises a sensor terminal node, a wireless gathering node, a wireless body area network gateway, a personal terminal, a remote medical terminal and an information feedback system, wherein the sensor terminal node comprises a medical sensor, a signal conditioning circuit, a microprocessor unit and a wireless transceiver unit which are sequentially connected, the medical sensor sends collected data into the signal conditioning circuit for preprocessing, and the wireless transceiver unit is controlled to perform wireless transmission after the data is processed by the microprocessor unit; the data collected by the sensor terminal node sequentially passes through the wireless gathering node and the wireless body area network gateway and is respectively transmitted into the personal terminal and the remote medical terminal, and the data is transmitted into the information feedback system after being processed by the remote medical terminal, and is displayed by a 3D model built through the information feedback system. The monitoring system can be used for monitoring the exercise rehabilitation situation of a patient in real time, providing reasonable guidance and advices for subsequent rehabilitation training and improving the rehabilitation training effect.

The invention discloses an evaluation method of a leather-making industry technology based on a fuzzy comprehensive evaluation method. The method comprises the steps of: utilizing a multi-index hierarchy analysis method and fuzzy comprehensive evaluation in the evaluation to consider the influence factors such as economy, society, environment and performance and the like, and on the basis of establishing a multi-hierarchy evaluation index system, combining a multi-hierarchy index weight analysis method and the fuzzy membership concept of uncertain indexes in fuzzy mathematics. In the evaluation method, the comprehensive and reliable evaluation can be carried out on the whole production process of the leather-making industry, and effective technical support can be provided for environment management such as the evaluation on environmental influence of the leather-making industry, engineering design, construction, inspection and acceptance, operation management and the like.

The invention discloses a system and method for quickly inspecting a tunnel defect based on machine vision. The system is arranged on an investigation bearing vehicle. The system comprises a machine vision sub-system used for acquiring the to-be-investigated object image data by a CCD (Charge Coupled Device) camera, a laser ranging sub-system used for measuring an imaging distance of an image acquired by the machine vision sub-system by a laser ranging method, a photoelectric speed measuring sub-system used for providing a corresponding coordinate of the acquired image in a tunnel, a control sub-system used for controlling the laser ranging sub-system and the photoelectric speed measuring sub-system, transmitting the data acquired by the laser ranging sub-system and the photoelectric speed measuring sub-system to a data processing sub-system and triggering the machine vision sub-system to acquire an image and transmit the image to the data processing sub-system, a data processing sub-system used for processing the image acquired by the machine vision sub-system according to the data from the control sub-system, and a power supply sub-system used for providing voltage for other sub-systems. According to the invention, the general tunnel defect can be regularly and quickly inspected and the inspecting process is safe, quick, full-automatic and real-time without influencing normal work of the tunnel.

The invention discloses a method based on generalized GPS data for determining passenger-waiting station alternative addresses of taxis. The method includes firstly, obtaining the pickup position GPS data and call service data of the taxis by collecting and preprocessing the generalized GPS data of the taxis; secondly, clustering the pickup position GPS data of the taxis according to different traffic service regions, taking cluster centers as initial alternative station addresses and achieving the visualization of the initial alternative station addresses; thirdly, determining frequently-used call service positions according to the call service data and achieving the visualization of the frequently-used call service positions; and lastly, selecting the focuses of all the call service positions within the service ranges of the initial alternative station addresses as the passenger-waiting station alternative addresses of the taxis. Compared with an existing method for determining the passenger-waiting station alternative addresses of the taxis, the method based on the generalized GPS data for determining the passenger-waiting station alternative addresses of the taxis has the advantages of manpower and material resource saving, good persistency and good combination with the development tendency of the industry.

The invention relates to a different sound on line detector for speaker based on time-frequency analysis. The invention is mainly characterized in that a signal generator is connected with a speaker through the wires, wherein the speaker is arranged in the heat transmission hole at the top of a noise elimination box, the bottom of the noise elimination box is provided with a microphone, the microphone is corresponding to the speaker, the microphone is connected with the input end of a collection card through wires, and is passed through A/D conversion, wave filter, time-frequency conversion, fault classification and identification, then outputs the identification results. The invention has a simple whole structure, the installation and manufacturing costs are lower, by adopting the method of time-frequency analysis, the speaker realizes rapidly and automatically intelligently detection in the production line, and the detection is precise, the detection efficiency is higher, the invention effectively overcomes the subjective and described fault identification by detector according to the experiences, and effectively ensures the healthy of the detectors; In addition, the invention is equally applicable to all the tuning of musical instruments, audio detection of pitch, so as to guarantee precise and reliability of the tuning and pitch of the musical instruments.

The invention discloses a multiple combination optimization overhead transmission line operation risk informatization assessment method which comprises the steps that 1. risk identification is carried out, wherein by data collecting, a fault source is found, a risk accident set is generated, an uncertain risk factor set is analyzed in a statistic mode, and a risk evaluation index system is established; 2. an integrated risk value is determined, a transmission line operation risk assessment model is established, information entropy and an analytic hierarchy process are fused, risk probability, consequences generated by risks and risk weight are considered in a comprehensive mode, risk consequence severity is quantized through a mutual information value, and a transmission line operation integrated risk value is computed in a layer-by-layer-reasoning mode and a multiple-combination mode; and 3. risk determining is carried out, risk grades are divided, analyzing is carried out on the integrated risk weight, the risk grades are determined, and the results of risk assessment are output. According to the method, the overhead transmission line operation risk is assessed in a comprehensive mode and a multilevel mode, and the accuracy of transmission line operation risk assessment and the reliability of transmission line operation are improved.

The invention relates to a fully-automatic stock operation server, belongs to the field of computer server, and aims to realize automated stock operation with a high success rate and stable profit. The fully-automatic stock operation server consists of an IE client browser, an MT4 or stock trading software, HTTP web server software, a core database, a scheduling program, an MQ4 intelligent trading program developing platform, a stock software background developing platform, and a stock operation core control program. The fully-automatic stock operation server has the advantages of automatic stock operation, capability of overcoming subjective and emotional errors of artificial market analysis and stock operation, high success ratio, high stability and high profit; the core stock operation algorithm of the system is tested by long-term historical data and real-time data, which proves that stock operation profit success ratio is over 90 percent, the profit curve straightly rises, the annual investment return is over 50 percent, and the fully-automatic stock operation server is suitable to be used by people engaged in investment and market analysis of financial security.

The invention belongs to the field of marine applied acoustics. In order to provide a new artificial classification method for underwater acoustical signals with stable classification results, low workload, good subjectivity, accurate feature extraction, high classification accuracy, and good adaptability, the invention provides a whale and dolphin Click-like sound and traditional sonar signal classification method and device. The device includes three subsystems: a signal preprocessing subsystem, a signal time-frequency feature extraction subsystem, and a signal time-frequency feature classification subsystem. The signal preprocessing subsystem comprises: a hydrophone, a sound storage medium, a sound de-noising module and an endpoint detection module. The signal time-frequency feature extraction subsystem comprises a signal short-time Fourier transform preprocessing module, a signal time-frequency contour extraction module, a signal time-frequency contour curve fitting and signal time-frequency feature extraction module. The whale and dolphin Click-like sound and traditional sonar signal classification method and device are mainly applied to marine applied acoustics.

The invention discloses a credit evaluation method based on an AHP (analytic hierarchy process). The credit evaluation method based on the AHP includes: confirming a credit evaluation grade set; confirming a multilevel evaluation index, and constructing an index evaluation system of a four hierarchy structure formed by an overall objective layer, a criterion layer, a discrimination layer and an index layer according to the confirmed evaluation index; confirming value ranges of the evaluation index of the index layer according to three modes of using an actual number, a percentage and a status value; using a matrix judgment method to calculate the weight of the evaluation index according to the importance degree of the evaluation index and structural relationships among the four layers, confirming the value of the evaluation index according to information which constitutes an index element, and then using a preset subordinating degree function to calculate the subordinating degree valued of the evaluation index according to the value of the evaluation index; using the AHP to evaluate the credit grade of an evaluated object. The credit evaluation method based on the AHP has the advantages of being objective, scientific and accurate, and can be widely used in the credit evaluation field.

The invention discloses a multi-target planning method for power grids of wind farms based on improved NSGA-II. The multi-target planning method includes the steps of building an output force model of the wind farms, calculating the flicker value of a wind turbine generator system at a common connection point, creating a target function with shortest line length and minimal flicker value of a wind farm at a common access point, and realizing multi-target planning of the power grid of the wind farm based on NSGA-II algorithm of NDX operators, the output force model and the target function. The multi-target planning method overcome the defects of subjectivity of conventional multi-target optimization and obtaining one solution in one time, enhances overall searching capability than routine NSGA-II algorithm, and improves convergence.

The invention discloses a chaos-based method for detecting and classifying early single-point faults of a mechanical component. The method comprises the following steps of: processing conventional sample fault signals in different states of the mechanical component to establish check intervals for different fault types; acquiring fault characteristic frequencies corresponding to all single-point fault states of the mechanical component to construct a frequency matrix of a Duffing chaotic oscillator; solving critical thresholds of periodic driving force amplitudes corresponding to different fault characteristic frequencies to construct a frequency-threshold matrix; and finally, adding a signal to be detected to calculate the maximum Lyapunov exponent matrix M, checking according to data inthe M, calculating correlation dimension of the signal to be detected if a fault signal is available, and classifying the faults to determine a fault mode in comparison with the established correlation dimension intervals for different fault types. By adopting the method, the early single-point faults of the mechanical component are detected and classified; and the method has high noise resistance capacity and extremely high fault detection success rate.

A TCM (Traditional Chinese Medicine) complexion automatic sorting method applying a superficial layer neural network belongs to the field of computer vision. The designed superficial layer neural network has five layers and adopts three different layer structures including an input layer, a characteristic extraction layer and an output layer. The input layer is composed of a convolution layer and a rectified linear unit (ReLU). The characteristic extraction layer is composed of three layers of network, wherein each of the first two layers is composed of a convolution layer and a ReLU activation function; one of the convolution layer and the ReLU is subjected to batch normalization and a pooling layer is added behind the second ReLU of the characteristic extraction layer; the third layer of the characteristic extraction layer is a whole connection layer connected with a ReLU in a followed manner. The output layer is composed of the whole connection layer and is provided with a followed softmax sorter. The method provided by the invention is distinctively advantaged in sorting precision and has invariance property in distortion such as zooming, translation, rotation and the like, is high in robustness and capable of improving sorting precision effectively. Therefore, the depth learning theory is applied to TCM face diagnose objectivity study.

The invention discloses a quality evaluation method of life cycle assessment data. The method comprises following steps of dividing original list data of an assessment object into direct list data and indirect list data; calculating the uncertainty of the list data by taking the original data as a normal distribution function and by using the relative standard deviation of the original data according to the average value of the original data, and the upper change limit range and lower change limit range of the data; obtaining the uncertainty of summarized list data of a full life cycle by utilizing a data error transfer theory; and finally through combination of a pollutant environment influence type classification method, obtaining the uncertainty of classified environment influence loads. According to the method provided by the invention, through adoption of three levels of uncertainty indexes of the list data uncertainty, the summarized list uncertainty and the environment influence load uncertainty, reliability evaluation of the full life cycle assessment results is realized. According to the method provided by the invention, the subjectivity in the quality evaluation process of the life cycle assessment data is reduced, and the problems that stochastic simulation computation is high in complexity and great in computation amount are solved.

The invention discloses a visuoauditory brain-computer interface-based consciousness state detecting method. The method includes the following steps of: 1) interface design; 2) signal acquisition; 3) detection; 4) data processing; and 5) result statistics and evaluation. According to the method of the invention, a visuoauditory brain-computer interface is adopted, so that the possibility of the detection of reserved cognitive function and potential consciousness can be improved. Two digital keys blink in a random order, so that visual related ERP potentials are generated, at the same time, two pieces of digital sound simultaneously appear, so that auditory related ERP potentials are generated; visual and auditory stimulus which appears simultaneously will produce a visuoauditory integration effect; Compared with a visual brain-computer interface and an auditory brain-computer interface, the method can improve the precision rate of a system and increase ERP response waveforms, and therefore, the validity and accuracy of the system can be improved, and services can be provided for consciousness state detection clinic and research.

The invention discloses a method for assisting evaluation of visual positioning based on a brain-computer interface system. The method comprises the steps of 1) stimulating selection, arrangement andexperimental paradigm design; 2) signal acquisition; 3) data processing; 4) statistical test evaluation standard. The method is combined with a behavioral scale evaluation form of CRS-R, a visually newfangled (oddball) paradigm BCI system is constructed to guide a subject so as to stare at a moving target stimulus and score visual positioning according to electroencephalography response, and the accuracy and objectivity of scoring are ensured.

The invention provides a discrimination method for caramel sweet taste characteristics of a tobacco leaf based on flavor components. The discrimination method is characterized by comprising the following steps: (1) establishment of a sample database of tobacco leaves with caramel sweet taste characteristics; (2) artificial discrimination of the caramel sweet taste characteristics; (3) establishment of a flavor component database of the tobacco leaves with the caramel sweet taste characteristics; (4) screening of flavor component characterization indexes of the tobacco leaves with the caramel sweet taste characteristics; (5) establishment of a model for discrimination of the caramel sweet taste characteristics by using the flavor components of the tobacco leaves; (6) testing of the model; (7) determination of flavor components of an unknown sample; and (8) discrimination of caramel sweet taste characteristics of the unknown sample. The invention has the following advantages: the model for discrimination of caramel sweet taste characteristics based on flavor components is established, the problems of subjectivity and nondeterminacy of determination which is carried out mainly through subjective recognition of a smoke panel in the prior art are overcome, and scientificalness, objectivity and accuracy of determination of taste characteristics are improved.

The invention provides a tea leaf grade identification method based on an image recognition technology. The tea leaf grade identification method comprises the following steps: brewing tea leaves with different grades, and leaching tea soup; flatly paving the expanded tea leaves on a fixed transparent film with known area; scanning to obtain a tea leaf image; programming the tea leaf image by using matlab software and converting the tea leaf image into a black and white binary image; and calculating the ratio of black and white pixels in the image to accurately obtain the surface area of the tea leaves. SPSS data statistic analysis software is used for carrying out single-factor variance analysis on the surface area of the tea leaves with the different grades, the significant difference p value is less than 0.05, and the tea leaves with the different grades are obviously different. A tea leaf grade predication model is established through a method for gradually and linearly judging. The novel method for identifying the tea leaf grades is provided for rapidly and accurately determining the surface area of the tea leaves with the different grades based on a scanning-image recognition technology.

The invention discloses a remote sensing image quality evaluation method based on phase congruency, and aims to overcome the defect in the prior art that the remote sensing image quality is only represented through a single parameter. The remote sensing image quality evaluation method comprises the following steps: (1) inputting a remote sensing image to be evaluated; (2) acquiring a phase congruency value of the remote sensing image in a strip noise direction; (3) performing binarization processing on the phase congruency value; (4) acquiring a strip noise intensity matrix; (5) calculating a strip noise value; (6) acquiring ordinary noise information; (7) calculating an ordinary noise value of the remote sensing image; (8) calculating an ambiguity value of the remote sensing image; (9) acquiring a comprehensive evaluation value of the remote sensing image by using a choquet ambiguity integral; (10) outputting the comprehensive evaluation value of the remote sensing image. The remote sensing image quality evaluation method has the advantages that no reference is needed, the quality of the remote sensing image can be comprehensively evaluated, and the evaluation result can relatively well accord with subjective evaluation.

The embodiment of the invention provides a labeling quality detecting method and device. The method comprises the following steps: acquiring a label image of a label to be detected; carrying out image pre-processing to the label image, wherein the image pre-processing at least comprises grayness processing; acquiring gray features of a feature point, in a set position, of the label image processed through image pre-processing; matching the gray features with the gray features of a corresponding feature point of a standard label image, and determining whether the label to be detected is qualified or not according to matching results. According to the scheme, manual visual detection is replaced by the acquisition of the gray features and the matching of the gray features, defects of strong subjectivity, high misjudgment ratio, low detection efficiency and the like of manual visual detection can be overcome, the detection precision to the labeling quality is improved, and the detection efficiency is improved.

The invention provides an expansion curve analysis method for a steel critical point test and a use thereof. The expansion curve analysis method comprises drawing an expansion curve by temperatures T as horizontal coordinates and expansion amounts L as vertical coordinates in data recorded by a dilatometer, respectively carrying out linear fitting on linear expansion parts at the left and right sides of the expansion curve to obtain straight line equations L alpha and L gamma of the corresponding expansion amounts and temperatures, calculating a high temperature phase (gamma phase) volume fraction X gamma, drawing a curve by T as a horizontal coordinate and X gamma as a vertical coordinate, selecting an appropriate critical volume fraction C according to concrete experimental requirements, finding temperatures T respectively corresponding to two points with X gamma equal to C and X gamma equal to 100%-C from the X gamma-T curve, wherein the temperatures T are used as critical points, and expressing test results comprising the transformation critical points and critical volume fractions C. The expansion curve analysis method solves the problem that the tangent method, the extremum method, the angular cut method and the average method have undefined physical significance or easily is influenced by a subjective factor, and improves an objective quantification degree of expansion curve analysis.

The invention discloses an intelligent pulse diagnosis method based on a three-dimensional pulse wave image. The method comprises the following steps: collecting multi-point pulse waves in the range of inches, cuts and feet of a patient at the wrist of a human body; constructing the digital dynamic three-dimensional pulse wave image according to the obtained multi-point pulse wave, using the obtained digital dynamic three-dimensional pulse wave images to carry out automatic disease diagnosis; and storing and displaying the raw data and diagnostic results. The invention can capture other smallcharacteristic signals in the target range besides the three points of the inch, the close point and the ruler, and automatically extract the space by using the depth learning model. Temporal association features are used to automatically judge the disease type.

The invention provides a rock and earth mass shear rheometer taking rainfall and blast vibration reciprocal actions into account. The rock and earth mass shear rheometer comprises a shear rheology unit, a dry-wet cycle unit, a blast disturbance unit and a CCD displacement automatic measurement system for detecting displacement of a lower shear box. The blast disturbance unit provides disturbance for the shear rheology unit through a rigid support and a vibration motor and simulates blast loads, and the rigid support is formed by a vertical supporting rod piece, an upper rigid rod piece and a lower rigid rod piece. The connecting positions of the vertical supporting rod piece and the upper rigid rod piece and the lower rigid rod piece are adjustable, and the disturbance transmitted to a pressurization system is adjusted to achieve disturbance loads of different strengths and quantitative simulation of blast loads in the rheological test process. According to the rock and earth mass shear rheometer taking the rainfall and blast vibration reciprocal actions into account, blast loads and rainfall reciprocal actions of different frequencies, strengths and periods can be effectively simulated in the shear rheological test process, and displacement change conditions of a sample in the test process are measured accurately to be used for quantitative research on shear rheological characteristics of rock and earth mass under the rainfall and blast vibration reciprocal actions.

The invention provides a network health degree testing method and a network health degree testing system. The method comprises the following steps of: acquiring multiple characteristic values of a network; setting preset health degrees for characteristic combinations of the characteristic values respectively; calculating the maximum entropy value of each characteristic combination based on the maximum entropy principle; and taking the preset health degree of the characteristic combination corresponding to the maximum entropy value as the health degree of the network. The sorting operation state of the current network is obtained aiming at the operation characteristic of the current network by acquiring the conventional network states and using the maximum entropy principle and finally revealed in a form of health degree, so that evaluation of the network health degree is realized, subjectivity and inaccuracy of human evaluation are overcome, and the problem of difficult human evaluation under the complex network condition is solved.

The invention belongs to the field of structural engineering. The technical problems to be solved are to overcome the shortcomings of the prior art and provide a relatively more precise method for determining the calculated length of a primary steel member with a large-span spatial structure and complicated boundary conditions. The method comprises the following steps of: 1, performing characteristic value buckling analysis on an integral structure under load control working condition to obtain the buckling mode of each order; 2, applying minor geometric imperfection by taking a rod piece destabilization mode obtained by the characteristic value buckling analysis as an initial state of form, and performing geometrically nonlinear elastic bearing capability process analysis on the integral structure; 3, in a bearing capability losing process of the integral structure, tracking the axial force-displacement changing conditions of a rod piece, and judging the occurrence of a critical load according to whether an axial force reaches a maximum value and is declined or not; and 4, determining the calculated length of the rod piece according to a formula, wherein the steps are finished by a computer.

The invention, which belongs to the field of photovoltaic power generation, provides a resistance-calculation-based fault diagnosis method for a photovoltaic string. The method comprises: step one, data point sampling is carried out by means of voltage modulation, series and parallel resistors of the string are calculated, and relevant data are uploaded to a data analysis platform; step two, datachanging rules and features of the series and parallel resistors are extracted, a fault type determination and degree assessment model is established, and then comparison and analysis are carried outon the series and parallel resistors of the string, so that fault type determination and degree assessment of the string are carried out; step three, according to a fault diagnosis result, a fault report is issued and the operation and maintenance are guided; and step four, the relevant data are stored into a database and the fault diagnosis model is optimized regularly. Therefore, on-line automatic diagnosis of the fault of the photovoltaic power station string is realized; shutdown during the diagnosis process is avoided; and the influence on the power generation state of the power station is reduced. And subjectivity and instability of the manual inspection are eliminated; the fault is processed quickly, accurately, and efficiently; the labor cost is lowered; and the operation and maintenance efficiency is improved.

The invention discloses a method and device for automatically observing fire in an aluminum electrolytic cell. The method comprises the steps of (1) obtaining a fire eye image of the aluminum electrolytic cell and converting the fire eye image into a fire eye digital image, (2) preprocessing the fire eye digital image, (3) converting the preprocessed fire eye digital image into a fire eye gray image and constructing a gray image matrix, (4) using a multiple-threshold cutting method of a gray value to carry out function area division on the fire eye gray image according to the gray image matrix in the step (3), (5) extracting a fire eye information index of the function area in the step (4), wherein the fire eye information index is at least one item in area, temperature and a texture feature value, and (6) displaying the fire eye image and fire eye information to realize automatic fire observation. Through the above method, the fire eye image can be obtained, a fire eye appearance condition and hidden information can be rapidly and accurately obtained, and the automatic fire observation function of the aluminum electrolytic cell is realized.