88results about How to "Avoid the influence of human subjective factors" patented technology

The invention discloses an environment risk source pre-warning system, comprising a data collector, a data server, a risk real-time evaluation system and a warner. The data collector is used for collecting real-time monitoring data of detection points in an environment risk source. An environment risk source information database for recording environment risk source basic information and a threshold value database for recording the threshold values corresponding to the real-time monitoring data of the detection points are installed in the data server. The risk real-time evaluation system is used for carrying out security evaluation on the environment risk source and calculating the risk degree of the environment risk source. The warner is used for carrying out selective warning according to the risk degree of the environment risk source. According to the system, the risk evaluation and pre-warning can be carried out on the environment risk source, a monitor can be helped to take countermeasures effectively and timely, and losses resulting from a risk event can be reduced to the lowest.

The invention relates to a thyroid CT image computer-aided diagnosis system and method. The problem that currently, many defects exist in the thyroid disease diagnosis through physical examination, ultrasonic scanning and radioisotope scanning is solved. The system comprises an input module, an image texture characteristic extracting module, a classified diagnosis module and an output module which are sequentially connected. The method includes the steps of conducting outline segmenting and extracting on an image, then conducting texture characteristic analysis on the image to obtain the 28-dimension texture characteristic, and finally substituting the 28-dimension texture characteristic into a diagnosis model to obtain a diagnosis result and a statistics index. The thyroid CT image computer-aided diagnosis system and method have the advantages that non-invasiveness, rapidness and timeliness are achieved; no chemical reagents or the like are needed, and cost is low; complexity of a lesion thyroid texture characteristic sample set is effectively reduced, and identification accuracy can be further improved; the result is not affected by man-made subjective factors and is prevented from being affected by man-made subjective factors in the pathological examination and other examinations.

The invention discloses a risk assessment system based on a fuzzy matrix analytic hierarchy process. The system comprises an assessment index system generation module, an assessment level system generation module, an index quantification module, a index weight calculating module, a membership degree matrix construction module, a fuzzy comprehensive result calculating module and a risk assessment module, wherein the risk assessment module comprises a risk situation assessment sub-module, a risk analysis sub-module and a risk control sub-module. The risk assessment system based on the fuzzy matrix analytic hierarchy process of the invention can analyze various uncertain factors and indexes appearing in the risk assessment process by using the fuzzy matrix and the analytic hierarchy process (AHP) in the risk assessment.

The invention discloses a method and a device for the characteristic analysis of a human body based on shoes wearing footprint images, and belongs to the technical field of criminal investigation. The method comprises the following steps: S1, preprocessing the shoes wearing footprint images: removing the interference on shoe sole patterns in the shoes wearing footprint images through an image filter operation, wherein the dimension of the filter is determined according to the size of the pattern adaptively; S2, carrying out multi-layer pressure surface extraction on the shoes wearing footprint images; S3, obtaining the morphological characters of the footprints; and S4, building mathematic models between the morphological characters and stature, age, posture and posture; and obtaining the characteristics of the human body. According to the method provided by the invention, the characteristic analysis of the human body can be realized automatically, and the characteristic analysis of the human body can be analyzed stably and precisely without the influence caused by the dimensions of the shoe sole patterns.

The embodiment of the invention discloses a target area contour determination method and device based on an electronic map and a storage medium, and belongs to the technical field of computers. The method comprises the steps of obtaining an electronic map; establishing an interest point set according to interest point data of which the region identifier is the same as the region identifier of thetarget region; taking the unit area with the unit area identifier identical to the unit area identifier corresponding to the position information of each interest point as a unit area to which each interest point belongs; combining a plurality of mutually communicated unit areas in the unit areas to which the plurality of interest points belong to form a communicated area to obtain a plurality ofcommunicated areas, and selecting a target communicated area of which the area is greater than that of other communicated areas from the plurality of communicated areas; and determining the contour ofthe target connected region as the first contour of the target region. The contour of the target area does not need to be manually determined, the influence of artificial subjective factors is avoided, the accuracy of the contour is improved, and manpower resources are saved.

The present invention relates to a wideband dielectric impedance spectroscopy method-based XLPE cable insulating property assessment method. The technical characteristic is that the method comprises the steps of processing an XLPE cable insulating sample into a wafer-shaped sample; cleaning the wafer-shaped sample in the absolute ethyl alcohol, and then carrying out the ultrasonic cleaning processing; coating the conductive silver colloids in the circular areas at the symmetrical positions of the upper and lower surfaces of the wafer-shaped sample; carrying out the wideband dielectric frequency spectrum test after the conductive silver colloids dry; comparing and analyzing the wideband dielectric frequency spectrum test results to obtain an XLPE cable insulating property assessment result.The method of the present invention can carry out the wideband dielectric impedance spectroscopy test on the XLPE cable insulating sample, analyzes the insulating aging performance of the XLPE cableinsulating sample and avoids the influence of the human subjective factors, and a test result determination method is simple, convenient and rapid, is high in accuracy, provides the technical supportfor accurately assessing the service life of an electric power cable and improving the service life of the electric power cable and has the important significance for improving the cable power supplyreliability and reducing the operation and maintenance cost.

The invention discloses a city edge region extraction method based on multi-source data fusion, and the method comprises the steps: selecting a plurality of pieces of city edge feature data as data sources, and respectively determining a city edge region recognition index factor of each piece of city edge feature data; after data standardization processing is carried out on the urban edge area identification index factors, calculating index values and index weights of the urban edge area identification index factors, and obtaining urbanization characteristic values through calculation of the index values and the index weights; performing urban edge area mutation point identification and extraction according to the urbanization feature value to obtain an urban edge area mutation point cluster; performing spatial position and attribute feature clustering on urban edge area mutation point clusters, performing inner and outer boundary extraction on each clustering cluster, and obtaining urban edge area boundaries. By the adoption of the city edge area extraction method based on multi-source data fusion, automatic extraction of the boundary of the city edge area is achieved, and the boundary recognition precision of the edge area is improved.

The invention discloses a lung CT image computer aided system and method based on cluster analysis. The method comprises extracting the nine textural features of a lung CT image including energy, entropy, correlation, difference moment, contrast, sum average, variance, difference, and difference average based on a gray-level co-occurrence matrix; dividing samples into a training set and a verification set according to a ratio of 3:1; subjecting original high-dimensional data to dimensionality reduction by using an improved U-reliefF feature weight calculation method and calculating the corresponding weight values of respective textural features; and applying the weight values to an improved Weightedk-means algorithm to construct a nodule classification model. The method finds, by combininga plurality of textural parameters, that the combination of energy, contrast, entropy and correlation has the best classification effect, achieves a recognition rate of 81.18% of benign nodules and 91.48% of malignant nodules, has a good benign and malignant nodules recognition rate, and contributes to the early diagnosis of the lung cancer.

The invention discloses an underground metal mine goaf hazard degree grading evaluation method, which comprises the following steps: firstly, selecting 16 indexes to construct an underground metal mine goaf hazard degree grading evaluation index system, dividing hazard degrees into four grades, and determining a grading standard; then, determining the comprehensive weight of each index by adoptingan AHP, entropy weight method and game theory combined weighting method; establishing a matter element extension model for goaf risk degree evaluation; substituting the weight value of each evaluation index into the matter element extension model to obtain each index correlation degree and a comprehensive correlation degree value which belong to each risk degree grade; and finally, determining the danger degree level according to the maximum correlation degree principle. According to the method, the goaf hazard level can be evaluated comprehensively, objectively and accurately, the evaluationprocess is clear, the evaluation result is objective, and a new method can be provided for grading evaluation of the underground metal mine goaf hazard level.

The invention relates to a method for predicting poverty degree of students based on machine learning. Through obtaining the data of students' relevant channels, we analyze the data and calculate thevarious eigenvalues of students' poverty, fill the missing values, standardize the data and map them to fixed intervals. Then, according to the fast clustering algorithm, we use Euclidean distance toaggregate the data into multiple categories, and calculate the importance of each category to evaluate the degree of poverty. A matrix compose of each group of data after classification is divided into blocks according to that correlation, and finally the poverty comprehensive score is calculated accord to the matrix after the blocks, and the comprehensive score can be used for reference in the aid amount decision of the aid for the poor students, wherein the higher the score is, the poorer the aid is, and the more the aid is needed. The invention also provides several schemes for quickly discovering abnormal poor students and screening the causes of poverty from the data.

The invention discloses a method and a device for human body feature analysis and based on barefoot or stocking-wearing footprint images and belongs to the technical field of criminal investigation. The method includes the following steps: S1, performing multilayer pressure face extraction on the barefoot or stocking-wearing footprint images; S2, acquiring at least the following footprint form structure features including foot length, foot width, heel width, arc width and positions of lower-edge convex points of a sole stress surface according to multilayer pressure face images of barefoot or stocking-wearing footprints; S3, respectively establishing mathematic models between the footprint form structure features and body height, age, posture and gender; inputting the above form structure features into the mathematic models to acquire human body features. By the method and device, human body feature analysis can be realized automatically, and human body feature analysis is stable and accurate.

The embodiments of the invention disclose an audio detection method and device, and a storage medium. The method comprises steps of obtaining a maximum value and a minimum value of each audio frame ina to-be-detected audio; determining a target audio frame, wherein the target audio frame is an audio frame in which the difference between the maximum value and the minimum values is smaller than a first threshold; if the target audio frame is not the mute data, obtaining an energy value whose frequency is less than a preset frequency in the target audio frame, and the proportion of the energy value in the total energy value of the target audio frame; and when the proportion is greater than the first preset energy threshold, determining that the target audio frame is an audio breakpoint. In this solution, the audio frame of the audio breakpoint can be accurately obtained by using the maximum value and the minimum value corresponding to each audio frame, the energy value wherein the frequency domain of the target audio frame is smaller than the preset frequency, and the total energy value of the target audio frame, which avoids the influence of subjective factors and improves the accuracy of audio detection.

The invention relates to an XLPE cable insulation pureness evaluation method based on broadband dielectric impedance spectroscopy. The method is suitable for testing the pureness of an ultra-high voltage cable insulating material. The method comprises the steps that an XLPE cable sample is cooled; the XLPE cable sample is heated; cooling and heating are repeatedly carried out to acquire the XLPE sample subjected to repeated cold and heat cycle stimulation processing; and the XLPE cable insulation pureness is determined according to the change rate of the dielectric loss spectrum before and after cold and heat cycle stimulation of the XLPE cable sample. According to the invention, a broadband dielectric impedance spectroscopy test result is directly used to evaluate the XLPE cable insulation pureness; the insulation pureness performance of the XLPE cable can be analyzed; the influence of man-made subjective factors can be avoided; the test result determining method is simple and quick; and the method is of great significance to improve the cable test level, shorten the test time and improve the reliability of the cable power supply.

The invention discloses an electric power communication network risk assessment system, which includes a risk assessor and a plurality of electric power communication devices connected to the risk assessor through a network interface. The risk assessor comprises an electric power communication network evaluation index system generation module, an evaluation level system generation module, an index quantification module, an index weight calculation module, a membership degree matrix construction module, a fuzzy comprehensive evaluation result calculation module and a risk evaluation module. The electric power communication network risk assessment system of the invention can analyze various uncertain factors and indexes appearing in the risk evaluation process through the application of a fuzzy matrix and an analytic hierarchy process in the risk evaluation, and is high in evaluation speed and accuracy.

The invention discloses an urban marginal area identification method and system, and the method comprises the steps: c gridding obtained land utilization data, urban road data, night light data and POI interest point data, carrying out t weighted summation, obtaining an urbanization feature value of each grid, and optimizing the grid scale; extracting a sampling line to obtain an urbanization characteristic value space sequence curve; extracting mutation points based on spatial continuous wavelet transform, and eliminating false mutation points according to double standard deviation; constructing a triangulation network for all mutation points, deleting a global long edge and a local long edge, and clustering the mutation points based on regional attribute entropy; and finally, extractingthe boundary of the mutation point set in the clustering cluster based on a coarse edge criterion and a fine edge criterion so as to obtain the boundary of the identified urban edge region. Urbanization features can be expressed more finely and objectively, city edges with complex structures such as cavities can be identified, and the identification precision is improved.

The invention discloses a rapid air-tightness precision testing device and testing method for air tightness detection of an automobile-shifting power-assisting cylinder shell. The test device comprises a first sealing mechanism which includes a sealing seat and a fixing device, which can apply pressure to the workpiece on the sealing seat so as to be fixed on the sealing seat and seal the openingof the first direction; a second sealing mechanism arranged on one side of the first sealing mechanism, which can seal opening of the second direction of the workpiece on the sealing seat; a gas-tighttest mechanism which can inflate the inner cavity of the workpiece and conduct the air-tightness test. The invention meets the limit fixing requirement of the workpiece and the sealing requirement ofdifferent openings through two sealing mechanisms to make the inner cavity of the workpiece form an effective sealing space, so that the air-tightness detection can be carried out by the inflating and the gas-tight detector. The structure is simple, the detection operation is easy, matching with the static seal which is easy to realize, the reliability and the effectiveness of the seal are effectively ensured, and the accuracy of the test results can be ensured.

The invention discloses an unconventional natural gas fracturing effect evaluation and productivity prediction method based on principal component analysis. The method comprises the following steps: 1) establishing an unconventional natural gas fracturing effect evaluation and productivity prediction evaluation database; 2) standardizing the original data; 3) calculating a covariance matrix; 4) solving a characteristic value and a characteristic vector; 5) calculating a variance contribution rate and an accumulated variance contribution rate, and determining the number of principal components;6) determining m vectors of the principal component, and outputting a new data sample; 7) establishing a multiple linear regression model according to the new sample, and performing fitting simulation test on the established multiple linear regression model; 8) performing fitting simulation inspection; and 9) carrying out shale gas fracturing effect evaluation and productivity prediction by usingthe established multiple linear regression model. According to the method, the problems of low linear relevancy and data redundancy of original data, artificial subjective factors caused by the factthat an existing evaluation method needs a large amount of sample data and expert scoring and the like can be well solved, and the accuracy of unconventional natural gas fracturing effect evaluation and productivity prediction is improved.

The invention discloses a high temperature furnace capable of displaying and controlling a constant temperature area belonging to a heating device, comprising a furnace boy, a heat preservation layer, a hearth with a heating thread (rod) and a program temperature controller that controls the temperature in the hearth. The hearth is provided with a set of multi-point temperature sensor that is composed of more than one temperature sensors with different lengths. Each temperature detecting point of the set of the multi-point temperature sensor is arranged in the constant temperature area and is capable of moving from beginning to end, and correspondingly displays the actual temperature of each point in real time on a display screen. The advantages of the invention lie in that the specific position of the constant temperature area can be regulated randomly and indicated objectively as required and the accuracy of the left position in the hearth of the sample is ensured, which avoids influence of human subjective factor and improves precision and accuracy of detecting result.

The invention discloses a cloud service trust evaluation method based on multi-parameter interval number multi-attribute decision-making. The method comprises the following steps: first collecting QoS index data in a multi-parameter interval number form, and listing a decision-making matrix, converting an index value in the multi-parameter interval number form into a binary connection number, and then normalizing the decision-making matrix according to the cost type and the benefit type to obtain a normalized decision-making matrix; secondly, determining the QoS index weight based on the unknown weight setting of the attribute weight of the connection number; and finally performing the cloud service trust evaluation by use of a principle value model based on the normalized decision-making matrix and the QoS index weight. By use of the evaluation method disclosed by the invention, the QoS index data is collected in the multi-parameter interval number form and then normalized so as to guarantee the reality and the objectivity of the data; the index weight is determined based on the unknown interval number multi-attribute decision-making method of the attribute weight of the connection number, thereby improving the objectivity of the decision-making; the cloud service trust evaluation is performed according to the principle value model, the time complexity of the evaluation method is lowered. The evaluation method disclosed by the invention has strong objectivity and practicability.

The invention belongs to the field of smart city evaluation, in particular to a smart city evaluation method based on an entropy weight method. The present invention analyzes the index sub-item data of each index item, constructs an evaluation model, and adopts the entropy weight as the quantitative weight of the smart city evaluation index in the way of combining the quantitative index and the entropy weight, and makes a decision on the degree of intelligence of the smart city. Accurate analysis avoids the influence of human subjective factors, makes the evaluation results more objective and persuasive, and greatly improves the objectivity and persuasiveness of the smart city evaluation results. The present invention can analyze and obtain the comprehensive ranking of the intelligence degree of each city and the main influencing factors affecting the development of each city's intelligence, thereby providing scientific guidance and reference for the advancement and development of each city's intelligence.