57 results about "Subjective consciousness" patented technology

The present invention discloses a riding early-warning method and device. The method includes the following steps that: car driving parameters corresponding to a car taken by a passenger is obtained; and if it is determined that the car driving parameters do not satisfy a vehicle safety riding condition, preset early-warning processing operation is performed to alert and prompt the passenger, so that the riding safety of the passenger can be ensured. According to the prior art, a passenger needs to judge the safety of riding according to the subjective consciousness of the passenger, and no systematized and automated tailored taxi service safety evaluation criteria and early-warning mechanisms exist, while, with the riding early-warning method and device adopted, the situations in the prior art can be avoided; and when the current riding environmental security level of the passenger is low, corresponding early-warning processing strategies can be taken, and the riding safety of the passenger can be ensured.

The invention discloses an order relation method-entropy weight method-based county power grid evaluation method. The method comprises the following steps: 1, establishing an index system and obtaining index values; 2, classifying and normalizing the indexes; 3, determining the subjective weight of the index system; 4, determining the objective weight of the index system; 5, calculating the combined weight; and 6, calculating comprehensively to obtain an evaluation result. According to the order relation method-entropy weight method-based county power grid evaluation method, weighting is carried out through a combined weighting method, and the experience advantages of the experts or workers and the structures of the data of the indexes are combined, so that the evaluation result which is more reasonable than the result obtained through a single weighting method is obtained. The order relation method embodies the essential feature of the decision-making thought of people, and the construction of a judgment matrix and consistency check are not required for the decomposition, judgment and integration, so that the calculation amount is greatly decreased, and the method is easy to grasp and apply. The entropy weight method embodies the structural feature of the data, so that the method is simple and easy to realize. And the two methods can make up the disadvantages that the single subjective weighting method completely depends on subjective consciousness and the single objective weighting method completely depends on data structure.

The invention provides a method for identifying production place of tea by using infrared spectrum technology, which comprises the following steps: production place typical lines of tea in place of origin are constructed; B. detecting sample: tea samples to be detected are taken and detected under the same condition with the standard sample respectively to obtain standard mid-infrared spectrums, average deviations between the tea samples and reference tea in production place are calculated according to the spectrums, and difference values between the average deviations and the production place typical lines are calculated, if the difference value is within standard deviation range, the tea sample belongs to the production place, otherwise, the tea sample does not belong to the production place. The method has the following advantages: 1. the analyzing result is not affected by subjective consciousness, thereby providing an impersonal evaluation criterion; 2. according to similarity theory, the average deviation can represent the difference between infrared spectrums of tea more accurately; 3. component separation, extraction and the like on tea are not needed before detecting infrared spectrum of the tea, which simplifies the operation, greatly improves the analyzing speed and reduces the detecting cost without environment pollution.

The invention is applied to the field of image quality evaluation, and provides a comprehensive evaluation method for scanned image quality. The method includes: step S1, pre-processing scanned images; step S2, performing no-reference image quality evaluation of the pre-processed scanned images, and obtaining a no-reference image quality evaluation index D1; step S3, performing reference image quality evaluation of the pre-processed scanned images, and obtaining a reference image quality evaluation index D2; and step S4, calculating and obtaining an image quality comprehensive evaluation index D according to the no-reference image quality evaluation index D1 and the reference image quality evaluation index D2 and respective weights. According to the method, the image quality comprehensive evaluation index is provided, many evaluation indexes in the market are converged to one, the evaluation of the image quality by human subjective consciousness is replaced, and unified description of the image quality is realized.

The invention relates to a photovoltaic module cleaning method. The method comprises steps: 1) related data for decisive factors influencing whether the photovoltaic module is cleaned or not are acquired, the data are processed, and accurate values of the decisive factors which are a generation gain level, a sediment transport rate, a precipitation amount and a module masking rate influencing whether the photovoltaic module is cleaned or not are obtained; 2) the accurate values of the generation gain level, the sediment transport rate, and the precipitation amount obtained in the first step are fed to a first-stage fuzzy controller for processing, and an initial cleaning index, that is, the initial cleaning probability of the photovoltaic module, is obtained; and 3) the accurate value of the module masking rate obtained in the first step and the initial cleaning index obtained in the second step are fed to a second-stage fuzzy controller for processing, and a cleaning decisive index is obtained. Thus, a decisive data support is provided for cleaning of the photovoltaic module, the defect that the original photovoltaic module cleaning decision subjective consciousness is strong is broken, and thus, cleaning and maintenance of the photovoltaic power station module are more scientific.

The invention relates to the technical field of detection, in particular to an evaluation method for the black tea fermentation quality based on a near-infrared spectrum technology. The method comprises the following steps of preparation of black tea samples, collection of spectrum information, measurement of fermentation quality indexes, division of sample sets, pretreatment of spectrum information, screening of characteristic wavelength variables, establishment of a fermentation quality prediction model and prediction of all fermentation quality indexes. According to the evaluation method, sample pretreatment is simple, the fermentation quality can be accurately and quickly identified, the method is high in operability, and influence of subjective consciousness in artificial sensory organ evaluation and complex operation of a traditional chemical analysis method are avoided; the result is objective and accurate, the objectivity and accuracy of the black tea fermentation quality are improved, the theoretical basis is provided for further implementation of an automatic, intelligent and precise fermentation control technology, and the method has great realistic significance and application prospects in detection of tea quality indexes.

The invention provides a Pu-Er ripe tea recognition method based on an infrared spectrum, which is characterized in that: the method comprises the following steps: A, collect the infrared spectrum in a Pu-Er ripe tea and other typical black teas, process data and build a Pu-Er ripe tea spectrum characteristic basic; B, build a linear discriminator which distinguishes whether a tea is belonged to the Pu-Er ripe tea or not; C, recognize samples of the Pu-Er ripe tea: carry out a same pretreatment to a tea spectrum to check, project the processed data on the characteristic basic, carry out effectively recognize to the Pu-Er ripe tea by the discriminator. The Pu-Er ripe tea can be objectively and effectively recognized according to the differences of infrared spectrum which are caused by the differences of tea types in the invention. The Pu-Er ripe tea recognition method has the following advantages: 1, the analysis result is not affected by subjective consciousness, therefore, an objective evaluation criteria is provided; 2, before the infrared spectrum of the tea is checked, works such as component separation, extraction and the like are not needed to carry out to the tea, the operation is simple and convenient, analysis speed is increased greatly. The checking cost is reduced and the environment is not polluted.

The invention discloses an application anti-addiction method and device as well as a mobile terminal. The method comprises steps as follows: a runnable duration upper limit of a designated application is determined according to use information on the designated application by a local user or a plurality of users in a network, so that the user sets the runnable duration of the designated application according to the runnable duration upper limit; the runnable duration which is set by the user and smaller than the runnable duration upper limit is determined to be actual runnable duration of the designated application; the designated application is subjected to anti-addiction processing according to the actual runnable duration. With adoption of the technical scheme provided by the embodiment, the problems that the user sets the runnable duration of the application only based on subjective consciousness and the anti-addiction function is further affected are solved.

The invention provides a vehicle door-opening pre-warning system and a control method, and relates to the field of vehicles. The pre-warning system comprises a vehicle speed collecting module, a target exploring module, a vehicle block state collecting module, a vehicle body control module, an alarming device and a vehicle lock executing module; the vehicle speed collecting module is used for collecting the speed information of a vehicle and transmitting the speed information to the vehicle body control module; the target exploring module is used for collecting the target information in the rear of the vehicle and transmitting the target information to the vehicle body control module; the vehicle block state collecting module is used for collecting the vehicle lock open-close state information and transmitting the vehicle lock open-close state information to the vehicle body control module; the vehicle body control module is used for receiving and processing the speed information, the target information and the open-close state information, and sending a control signal to the alarming device or the vehicle lock executing module according to a processed result; the alarming device is used for receiving the control signal and sending an alarming signal according to the control signal; and the vehicle lock executing module is used for receiving the control signal and controlling opening and closing of a vehicle lock according to the control signal. The vehicle door-opening pre-warming system and the control method effectively reduce even avoid risks of collision occurrence when passengers or a driver opens a vehicle door without simply depending on the subjective consciousness, and have good reliability.

The invention discloses a tea fermentation degree identification method based on an infrared spectrum. In the method, the characteristics of the mid-infrared spectrum data in various typical teas with different fermentation degrees are extracted to obtain main characteristic factors in order to build a characteristic base, and a linear arbiter I of severely fermented tea is determined by a mittellinie method; then, the characteristics of the mid-infrared spectrum data of various typical moderately fermented teas and one mildly fermented tea are extracted, the characteristic base is built by the main characteristic factors, and a linear arbiter II of the moderately fermented tea is determined by the mittellinie method; and finally, the tea to be detected is successively projected on the two characteristic bases, and the fermentation degrees of tea are identified by the linear arbiter I and the linear arbiter II. In the invention, the fermentation degree of tea can be quickly, visually and correctly identified based on the difference of the infrared spectrum of the tea with different fermentation degrees and by virtue of an informatics method, thus the operation is simple, the detection cost is low, the environment is not polluted, and the analysis result is not influenced by subjective consciousness.

The invention relates to a method and a system for monitoring safe sleep. The system comprises a body moving detection module, a getting-in-bed judging module, a master control module and a door window and an electric device, wherein the body moving detection module is used for acquiring the body moving information of a target object and a bed pressure signal; the getting-in-bed judging module is used for judging if the target object has a getting-in-bed action; the master control module is used for judging if the target object enters a sleep period after the getting-in-bed action occurs and is used for selectively controlling the door window and the electric device under the sleeping state after the target object enters into the sleeping period. The method and the system for monitoring safe sleep provided by the invention can be used for automatically detecting if the target object enters the sleeping period and directly selectively controlling the door window and the electric device to enter the sleeping period after the human body enters the sleeping state, so that the problem of unnecessary continuous work of electric appliance caused by the target object entering the sleeping state in a non-subjective consciousness sleeping process can be avoided, the energy is saved and the indoor safety is increased.

The invention relates to the technical field of computers, in particular to a task distribution method of a financial system, a task distribution device of the financial system, electronic equipment and a storage medium. The method comprises the steps of obtaining a to-be-allocated task and corresponding task data; extracting address information and task category information of the task data, andmatching execution branches for the to-be-distributed tasks according to the address information and the task category information; and extracting an attribute tag of task data corresponding to the to-be-allocated task and an attribute tag of each employee in the execution network, and allocating an execution object to the to-be-allocated task according to the attribute tag of the to-be-allocatedtask and the attribute tag of each employee. According to the method and the device, scientific and reasonable task distribution can be realized, the influence of human factors or subjective consciousness on task distribution is avoided, and the task distribution efficiency and accuracy are improved.

The invention provides a scene mode setting method which is applied in first electronic equipment. The method comprises the steps of sending a scene mode request message in a preset way, receiving a scene mode setting instruction which is sent by second electronic equipment in the preset way according to the scene mode request message, and setting a current scene mode according to the scene mode setting instruction. Therefore, scene mode setting does not need manual operation of a user and can be realized through interaction between the first electronic equipment and the second electronic equipment without relying on subjective consciousness of the user.

The invention discloses a fatigue driving monitoring device, which comprises an image collecting module, an image processing and identification module, a speed detection module, a control module, a warning module and a storage module, wherein the image processing and identification module receives the human face image information sent by the image collecting module, carries out analysis processing, identifies the human face characteristic information in the images, compares the human face characteristic information with human face image templates in the storage module, and sends image comparison result information to the control module to be analyzed and processed, and signals are sent to the warning module according to the analysis processing results. The fatigue driving monitoring device has the advantages that an image processing and identification mode is adopted for objectively judging whether a driver is in the fatigue driving state or not, the judgment is not up to the subjective consciousness of use personnel or supervisory personnel, whether the driver is in the fatigue driving state or not can be detected as long as the driver generates the fatigue state even within the specified fatigue driving standard time, and in addition, the fatigue driving warning information is sent out for prompting the driver, so the fatigue driving early warning effect can be realized.

The invention belongs to the technical field of near-to-eye display equipment application, and discloses an eye movement tracking interaction method and system for near-to-eye display equipment. The method comprises the steps: carrying out the sight line tracking through an eye movement tracking module on the near-to-eye display equipment, carrying out the calculation of the obtained eye movementinformation, and mapping the eye movement information to the coordinate position of an optical imaging screen button of the near-to-to-eye display equipment; clicking the imaging screen button, and executing the interaction function program after interaction succeeds. Compared with blink selection of existing eye movement interaction, attention of a user in the interactive control process througheyeballs is greatly reduced, meanwhile, cognitive loads in subjective consciousness are reduced, and discomfort caused by inharmonious control over monocular blink muscles is avoided; Compared with gesture recognition interaction control, the method has the advantages that the concealment is high, the operation is convenient and fast, and the method is suitable for application scenarios with privacy requirements.

The invention relates to a quality evaluation method of color ink-jet paper based on multi-level grey relational evaluation. The quality evaluation method comprises the following steps of: selecting a plurality of types of the color ink-jet paper which needs to be evaluated, and measuring basic physical performances of the paper; selecting a professional photo printer to sequentially print professional test versions, color scales and images on paper samples; measuring attribute printing performance of the printed images by an instrument; based on modeling which applies the multi-level grey relation technology to a comprehensive evaluation system, analyzing a plurality of evaluation data of the paper samples, calculating the relation degree of each type of the paper samples, finally establishing a printing quality evaluation system of the color ink-jet paper according to a multi-level grey evaluation model and then testing sensitivity of the system; and distinguishing the relationship among various influence factors according to a relation degree matrix. The quality evaluation method has the following beneficial effects that: a qualitative and quantitative evaluation result is obtained by applying the model based on the multi-level grey system to quality evaluation of the color ink-jet paper, thus solving the difficult problem that the overall quality of the color ink-jet paper is difficult to be scientifically and accurately evaluated in the printing field, obtaining the scientific and quantized comprehensive evaluation result of the paper quality, reaching a more scientific and accurate effect without judgment depending on subjective consciousness of a person, and playing a certain reference role in establishment of quality standard of ink-jet printing of the color ink-jet paper.

The invention discloses a whitening effect judging method based on spectral imaging. The whitening effect judging method comprises the following steps: (a), acquiring a standard spectral curve; (b), acquiring the spectral feature curves of skin before and after whitening; (c), carrying out spectral analysis. The method is formed by perfectly combining a spectral imaging technology and a spectral analysis technology, and the spectral reflectivity curves of different positions of the skin can be obtained by the spectral imaging and analysis technology. As the spectral reflectivity curves of the pigment-free skin of different people in a waveband range of 450-650nm are basically consistent, the spectral reflectivity curve can be used as the standard spectral curve. The whitening effect is quantitatively evaluated through comparing the similarity of the spectral feature curves of skin before and after whitening and the standard spectral curve, the problems of uncertainty and slow evaluating speed of the existing whitening effect evaluating method depending on subjective consciousness are solved, and the purpose of rapidly obtaining the whitening effect is achieved.

The invention provides an electric power industry carbon emission right distributing method based on an improved entropy weight method. Going deep into the electric power industry carbon emission process, in combination with the influences of discharge emission intensity, comprehensively considering the encouragement mechanism of clean energy power generation orientation and promoting the green and low-carbon development of the electric power industry, the carbon emission right distributing scheme is more reasonable. With the aid of the entropy definition and properties in the information theory, rules between all index relation properties are excavated, information entropies are introduced to serve as effective value indexes of all factors of the carbon emission right distribution, artificial subjective consciousness interference can be effectively avoided, the logic relation among all the indexes is well reflected, and the distribution result is more accurate and is closer to reality. By improving the calculating method of the index effective values, it can be avoided that small differences of entropies probably cause the multiplication of entropy weights and the inconsistency ofthe entropies and transmitted information, and the problem that corresponding entropy weight numerical values are not stable when the entropies of traditional entropy weights are close can be well solved.

The invention discloses a method and a device for generating an operation order. The method includes that first, an operation order position column to be edited is determined, then operation order content information preset by a system is selected directly, the selected operation order content information is displayed in the operation order position column directly till all operation order position columns are edited by users, and finally the operation order is generated. By means of the method and the device, the users are not required to input detailed operation order content information manually and only need to select the operation order content information required by the users by triggering signals, and the operation order content information can be displayed in the determined operation order position columns automatically, therefore work load of the users is greatly reduced, and operation order filling efficiency is improved. In addition, due to the fact that the edited information is preset by the system and is not affected by man-made subjective consciousness, and the accuracy of the operation order is improved.

The invention provides an individual network security awareness grading quantitative evaluation method for the problems of fuzzy definition of network security awareness and lack of an effective assessment system and method at present. The method comprises three parts including subjective consciousness assessment, behavior ontology assessment and assessment decision making. In the subjective consciousness assessment part, individual information is obtained through questionnaire survey; four dimensions including information security awareness, information legal ethics, information security knowledge and information security capability are scored through an analytic hierarchy process; and scores of an individual user in the four dimensions are obtained. In the behavior ontology assessment part, computer and mobile phone user behaviors are scanned; a direct distance with the optimal user behavior is calculated; and the security levels of the user behaviors are judged through a random forest algorithm. By fusing the subjective consciousness assessment and the behavior ontology assessment, the individual network space security awareness level is assessed. An experimental result shows that the method can realize individual network security awareness grading quantization in combination with a machine learning method, the granularity is reduced from high to low and is not less than the4 level, and the grading accuracy is more than 95%. The method can be used for improving the comprehensiveness and universality of an individual network security awareness grading quantitative model,and has a certain practical value.

The invention discloses a semantic cognitive facial feature identification method, which comprises a semantic cognitive facial feature construction step: extracting a semantic cognitive facial feature, and establishing a mapping relationship between the semantic cognitive facial feature and a facial action unit; a semantic cognitive facial feature extraction and computing model designing step: establishing a hierarchical, dynamic and multi-resolution semantic cognitive facial feature extraction and computing model according to external physiological properties of a face; and a semantic cognitive facial feature extraction realization step: realizing facial action unit detection and semantic cognitive facial feature extraction by utilizing a plurality of levels of threshold values and a hidden markov algorithm. According to the method, human cognitive experiences are used for reference for the external information representation of the face, so that the external information description of the face is more consistent with the subjective consciousness of a person. The method is used in the field of human-computer interaction and in particular for behavior comprehension in the field of multi-modal human-computer interaction.

The invention discloses a method for automatically generating a Bug repair plan and a Bug repair method, belonging to the field of computer software engineering. The method for automatically generating the Bug repair plan comprises the following steps: 1) using a resource modeling module to extract the attribute information of an input Bug report set; 2) using the resource modeling module to extract the attribute information of stored human resources; 3) using a task scheduling module to acquire a candidate human resource set required by each Bug repair activity in accordance with the extracted attribute information; 4) configuring a binary-system chromosome structure which can be identified by a genetic algorithm, wherein the binary-system chromosome structure comprises candidate resources of the repair activities and executed priority of the repair activities; and 5) using the task scheduling module to optimize the binary-system chromosome structure by the genetic algorithm to obtain the optimal repair plan of the input Bug report set. Through the invention, the accuracy of configuring the human resources is improved, the dependence on subjective consciousness of the human in the planning process is reduced, and the utilization rate of the human resources is improved.

The invention provides a probe used for carrying out realtime fluorescence quantitative RT-PCR detection of hog cholera virus, a primer sequence and a reagent kit containing the probe and the primer sequence. By means of the principles of the reagent kit and fluorescence quantitative PCR, the realtime fluorescence quantitative RT-PCR method for detecting hog cholera virus in animal food and animal-derived food is established; moreover, comparative study is carried out from aspects of sensitivity, specificity and so on. The detection method has the advantages of strong specificity, high sensitivity, excellent repeatability, simple operation, fast detection speed, no influence caused by subjective consciousness of operating staff, high flux of detected sample, low biosafety risk, and the like.

The invention discloses a short-term load prediction method based on a C-mean clustering fuzzy rough set. The method considers various types of influence factors influencing the short-term load prediction, collects the historical load data and the data of the load influence factors, performs the attribute reduction on the influence factors influencing the short-term load by using a fuzzy rough set, obtains a reduced environment attribute set influencing the short-term load, takes the attribute of the set as the input data and the short-term load as the output data to train a support vector machine model, and then uses the trained model for predicting the short-term load, so that the short-term load prediction method becomes faster and more accurate. According to the method, the problem that the membership function is selected in the fuzzy rough set due to the artificial subjective consciousness is solved, and the problem that the prediction speed and the prediction performance of the support vector machine are reduced due to the fact that an influence factor set is too redundant, is also solved.

The invention discloses a feature binning algorithm based on a decision tree. The algorithm comprises the steps of modeling a data sample, combining a feature variable and a target variable, setting alimiting condition, binning the decision tree and generating a binning result. The equipment provided by the invention can apply a machine learning decision tree algorithm to generate an optimal binning result under a certain condition, and the finally generated binning result achieves the optimal representation in data significance and eliminates the interference of subjective consciousness of modeling personnel. The algorithm is embedded into establishment of a traditional score card model or other emerging machine learning, the quality of a traditional credit model in the financial industry can be obviously improved, the approval accuracy is improved, and more fraud overdue applications are refused.

The invention discloses a short-term wind power prediction method for optimizing an SVM based on a segmented ant colony algorithm. The method comprises the following steps: selecting and preprocessing original sample data to eliminate the influence of dimensions on the original data, and the original data comprising M sets of environmental influence factors influencing the wind power output power and the wind power output power corresponding to the environmental influence factors; determining the structure of the support vector machine according to the processed data; carrying out segmented ant colony optimization on the kernel function parameters and the penalty coefficient C of the support vector machine by combining the structure of the support vector machine to obtain an optimal parameter combination of the SVM meeting the expected error; and according to the obtained optimal parameter combination of the SVM, constructing an SVM model, that is, a wind power prediction model, and utilizing the model to realize short-term wind power prediction. According to the method, the influence of artificial subjective consciousness selection on model parameter combination can be effectively reduced, and the method is not limited to be applied to wind power generation power prediction and can be applied to model prediction of other known historical data.

The invention relates to an oolong tea quality evaluating method based on the near-infrared spectrum technology. The oolong tea quality evaluating method includes steps of preparing tea powder samples, acquiring spectrum information, preprocessing the spectrum information, screening wavelength based on genetic algorithm, setting up an evaluation model and scoring oolong tea quality. The oolong tea quality evaluating method is simple in sample preprocessing, quality of oolong tea can be accurately and quickly evaluated, operability is high, influence of subjective consciousness in sensory evaluation and complicated operation of conventional chemical analysis method are avoided, and results are objective and accurate.

The invention discloses a motion reminding method, device and system, and belongs to the field of video processing. The motion reminding method comprises the steps that a three-dimensional model set reflecting the motion state of a moving object is generated according to collected motion images, and the three-dimensional model set comprises one or more three-dimensional models; feature informationof the three-dimensional model set is extracted; standard feature information corresponding to the three-dimensional model set is obtained; and when the difference between the feature information ofthe three-dimensional model set and the corresponding standard feature information is greater than a preset difference threshold value, reminding operation is executed. The problem that in the relevant technology, the posture correction process is mainly dominated by subjective consciousness of people, and consequently the accuracy of posture correction is low is solved.

The invention relates to detecting equipment and a detecting method for insulation and voltage resistance detection of a motor coil. The equipment comprises a case body, a transport mechanism, an automatic discharging insulation and voltage resistance detection mechanism, an air-drying mechanism, a material taking mechanism, a non-defective product dropping channel, a defective product dropping channel and a PLC control system, wherein the case is provided with a plurality of processing stations, a charge hole and a discharge hole; the transport mechanism is positioned in the case body for enabling the motor coil to transport among the plurality of processing stations; the automatic discharging insulation and voltage resistance detection mechanism and the material taking mechanism separately communicate with the PLC control system; after detected results are obtained, the automatic discharging insulation and voltage resistance detection mechanism is used for feeding back the detected results to the PLC control system; and when the motor coil is transported to the discharge hole, the PLC control system gives a material taking instruction to the material taking mechanism according to stored information, and carries out classifying according to the information. The detecting equipment can realize automatic sorting of non-defective products and defective products without human assistance, so that labor intensity of an operator is relieved, and misjudgment as a result of subjective consciousness of the operator is also avoided.