31results about How to "Extract reasonable" patented technology

The invention discloses a method for partial reference evaluation of wireless videos based on space-time domain feature extraction, which relates to a method for evaluating video quality. On the basis of performing profound understanding and detailed analysis on the existing video objective quality evaluation model, by combining visual characteristics of human eyes, the invention provides the method for the partial reference evaluation of the wireless videos based on the space-time domain feature extraction to improve the conventional SSIM model. The method takes the fluency of the time domain and the structural similarity and the definition of the space domain of the videos as main evaluation indexes, and under the condition of ensuring the evaluation accuracy, the method extracts characteristic parameters of ST domains (the space domain and the time domain), establishes a new evaluation model, reduces the reference data needed by the evaluation and lowers the computational complexity to ensure that the evaluation model is suitable for evaluating the quality of wireless transmission videos in real time.

The invention relates to a heat supply system for directly recovering sewage multi-section flashing steam waste heat by using multiple sections of absorption heat pumps, which is used for recovering sewage flashing steam waste heat. The system comprises 1, 2, ..., and N independent sealing chambers and the multiple sections of absorption heat pumps, wherein the multiple sections of absorption heat pumps comprise respective 1, 2, ..., and N generators, 1, 2, ..., and N condensers, 1, 2, ..., and N absorbers and 1, 2, ..., and N evaporators; water steam which is formed by flashing sewage in the 1, 2, ..., and N independent sealing chambers and has different pressure from high pressure to low pressure enters 1, 2, ..., and N evaporator tubes sequentially by 1, 2, ..., and N flashing steam and is directly connected with the 1, 2, ..., and N evaporators of the multiple sections of absorption heat pumps; and flashing steam condensate outflows the 1, 2, ..., and N evaporator tubes and reflows to respective 1, 2, ..., and N liquid phase areas of the 1, 2, ..., and N independent sealing chambers sequentially by respective 1, 2, ..., and N flashing steam condensate. The system can reduce heat loss, improve the water-supply temperature of hot water and reduce investment and running cost.

The invention discloses a human fall detection method based on triaxial acceleration. The method includes acquiring an acceleration set composed of all accelerations in two seconds before and all accelerations in a current second; determining an acceleration sequence for indicating suspected fall according to the acceleration set; acquiring a feature vector of the acceleration sequence for indicating the suspected fall according to the acceleration set; calculating a fall decision value according to the feature vector; judging whether a human body falls or not according to the fall decision value; and judging whether the fell human body is able to self-rescue or not according to an acceleration which is acquired at any acquisition time in alarm judgment time following all the currently acquired accelerations. The method is simple to implement, easy to calculate and high in detection accuracy.

The invention provides a night-vision video gait recognition method based on angle radial transformation and centroid. The method includes the following steps that: infrared video images are acquired; human body gait contours are extracted from the acquired infrared video images, and the extracted human body gait contour sequence is pre-processed; the gait energy graph of a human body is built according to the pre-processed human body gait contour sequence; the feature vectors of the gait energy graph is extracted, the angle radial transformation coefficient and centroid vector of the gait energy graph are adopted as the feature vectors; and the dimensionalities of the feature vectors are reduced through the principal component analysis method; and recognition matching is performed on the dimensionality-reduced feature vectors and a training sample set, so that the gait recognition of the infrared night vision images is realized. With the method provided by the invention adopted, the effective information of the gait energy graph of the night vision video images can be extracted effectively and effectively, the efficiency of the gait recognition can be improved, and the correct rate of the gait recognition can be improved.

The invention relates to a method of preparing pure natural chicken extract flavour liquid and the flavour liquid prepared by utilizing the same. The method of preparing chicken extract flavour liquid comprises the steps of taking chicken skeleton with low price as the raw material, curing and fermenting the chicken skeleton with curing agent at low temperature, distilling the body fluid of the fresh chicken in a water-resisting mode under the condition of pressure distillation to obtain distillate, removing the grease on the upper layer of the distillate by cooling, filtering the distillate to obtain transparent clear extraction, and heating and sterilizing the transparent clear extraction to obtain the chicken extract flavour liquid. The preparation process of the chicken extract flavour liquid provided by the invention is unique and is easy to realize and more reasonably and effectively extracts the natural chicken flavour components. The obtained chicken extract flavour liquid is rich of a great deal of amino acid and peptide components, contains no food additive, is transparent and has delicious taste and abundant nutrition.

The invention provides a spectral ellipsometry thickness non-uniform source depolarization effect correction modeling method and device, and the method comprises the steps: carrying out the measurement through a Mueller matrix ellipsometer, obtaining all Mueller matrix elements of a to-be-measured sample at a time, and obtaining the depolarization information of the sample. Then, by reasonable assumption of a distribution function with non-uniform thickness and full consideration of the non-uniformity of the thickness of each layer, reasonable nodes are selected and weight accumulation is performed to obtain a forward modeling average Mueller matrix of the sample; when the thickness distribution of each layer of the sample is random, Gaussian distribution nodes and weights are adopted, multi-dimensional calculation is simplified into one-dimensional calculation, and the calculation efficiency is greatly improved. Finally, fitting and information extraction such as optical constants andthickness values of parameters of the to-be-measured sample are carried out through a nonlinear regression algorithm. According to the invention, correction of a non-uniform thickness depolarizationeffect of spectral ellipsometry can be realized, rapid data analysis of on-line measurement in various optical thin film devices and various nanometer manufacturing processes can be realized, and optical and set parameters of the nanometer material can be extracted.

The utility model relates to a mine water waste heat extraction and utilization system, and belongs to the technical field of mine waste heat utilization. The mine water waste heat extraction and utilization system is characterized in that a heat pump water source unit (2) is included, the heat pump water source unit (2) is provided with a mine circulating water feeding pipe (3) and a water returnpipe (4), the heat pump water source unit (2) is connected with a mine water lifting device through he mine circulating water feeding pipe (3), the heat pump water source unit (2) is connected with awater return pool (5) through the water return pipe (4), and the mine water lifting device communicates with a downhole roadway (9). The mine water waste heat extraction and utilization system fullyutilizes the storage function of the abandoned roadway, realizes the purposes of temperature rise for energy storage in summer and heat release for energy release in winter of a roadway water body, reasonably stores, transfers and extracts energy, can maintain the operation of the water source heat pump unit, can realize zero discharge of external circulating water and is considerable in economicand social benefit.

The invention relates to the technical field of plant extraction, and particularly discloses an extraction method of lotus leaf polysaccharide. The extraction method comprises the steps: firstly, adding water into lotus leaves for extraction, and then performing enzyme extraction on a water extracting solution by using a compound enzyme consisting of cellulase, bromelain and pectinase to obtain apolysaccharide extracting solution; and carrying out alcohol precipitation, protein removal and decoloration on the polysaccharide extracting solution to obtain the lotus leaf polysaccharide. The lotus leaf polysaccharide is extracted by adopting an assisted water extraction method of the compound enzyme consisting of cellulase, bromelain and pectinase; the high yield of the lotus leaf polysaccharide is ensured, the content of the lotus leaf polysaccharide is increased, meanwhile, it is guaranteed that the lotus leaf polysaccharide further contains high active substances such as polysaccharideand general flavone, meanwhile, high immunocompetence is shown, a concise, efficient and reasonable process route for extracting the high-activity lotus leaf polysaccharide is researched, and a foundation can be laid for large-scale production and high-valued utilization of the lotus leaf polysaccharide.

The invention provides a power distribution network automatic construction investment benefit evaluation method, which comprises the steps of firstly selecting a power distribution network automatic construction investment index and a reliability core index; then performing 0-1 standardization or range standardization of the automatic construction investment index and the reliability index based on historical automatic construction investment and power outage data, so as to construct a difference type increment index and a ratio type increment index; performing pairing screening of a reliability index and automatic investment index combination based on a Pearson correlation coefficient and a Kendall rank correlation coefficient; and determining a final reliability index and automatic investment index pool; constructing an association model of an automatic investment index and a power outage reliability index through improved linear regression; then finally obtaining an automatic investment index version combination significantly influencing the reliability index by means of a goodness-of-fit coefficient and a significance weight coefficient of the improved linear regression, and obtaining a weight coefficient of the reliability index improvement degree of the automatic investment project.

The invention discloses an electromechanical product key quality characteristic determination method considering uncertainty, and the method comprises the steps: firstly determining the quality characteristic of an electromechanical product, then determining an influence factor and a sub-influence factor which influence the quality characteristic, and carrying out the evaluation of the quality characteristic through employing an interval q-run orthopair fuzzy set; performing consistency check and optimization on evaluation information given by experts; thirdly, calculating weights of the influence factors and the sub-influence factors; and finally, an interval q-run orthopar fuzzy accumulation proportion evaluation method is used for sorting the quality characteristics, and the key quality characteristics are determined according to a sorting result. According to the method, uncertainty and hesitation of expert evaluation information are considered, consistency check and optimization are carried out on the expert evaluation information, so that an evaluation result is more practical, the defects of a traditional key quality characteristic sorting method are overcome, and a basis is provided for control of key quality characteristics of mechanical and electrical products.

The invention discloses a method and a system for detecting abnormal power consumption behaviors of a power consumer. The method comprises the following steps: 1) obtaining user power consumption data through non-intrusive load monitoring; 2) processing the user power consumption data by adopting a deep Q network learning method to obtain a user power consumption behavior pattern pattern, wherein the user power consumption behavior pattern pattern comprises a checked abnormal user power consumption behavior pattern pattern; 3) extracting power consumption behavior characteristics from the checked abnormal user power consumption behavior pattern graph; 4) establishing a plurality of analysis models according to the extracted power utilization behavior characteristics; 5) adopting a Q network learning method to train and evaluate the plurality of analysis models, and selecting the analysis model with the optimal evaluation effect; and 6) detecting whether the power consumption behavior of the user is abnormal or not by adopting the analysis model with the optimal evaluation effect. Through monitoring and reasonable extraction and utilization of the electric energy data, reasonable power distribution of the power distribution network is facilitated, and the existing electric energy is used at the maximum efficiency.

The invention discloses a pi/4 compact polarization synthetic aperture radar building area extraction method, which reasonably extracts a building area by using compact polarization characteristics, and provides a new thought for the pi/4 compact polarization synthetic aperture radar building extraction method. The method comprises the following steps of: preprocessing pi/4 compact polarimetric SAR image data; obtaining a preprocessed pi/4 compact polarimetric SAR image, and calculating to obtain compact polarimetric features; calculating to obtain a water body extractor, an orthogonal building area extractor of which the building area is parallel to/perpendicular to the radar sight line direction and an inclined building area extractor of which the building area and the radar sight line direction have a large inclination angle by utilizing the compact polarization characteristics; a typical area is selected for statistical analysis to obtain thresholds of a water body extractor, an orthogonal building extractor and an inclined building area extractor, and the thresholds are used for extracting a building area to obtain a building area extraction result.

The water tackling method includes the steps of: using flow controlling apparatus to collect and drain water separating in the source; conveying water in separate pipelines, and finally processing and utilizing water separately. The present invention separates water in the source, conveys water in separate passages, processes water separately in high speed and high efficiency and utilizes water comprehensively. The present invention can solve the difficult problems of environmental pollution and lacking in water resource.

The invention discloses a monoamine oxidase enzyme activity detection kit and a use method thereof. The kit comprises an extract, a matrix buffer solution and a chromogenic substrate, wherein the chromogenic substrate is 4-p-dimethylamino benzylamine hydrochloride, and the matrix buffer solution is a PIPES buffer solution. The detection kit is suitable for samples such as animal tissues, serum (plasma), cells and the like, and is simple and convenient to operate, short in detection time, low in detection cost, environment-friendly and non-toxic.

The invention discloses a method for identifying the authenticity of purple sand teapot bottom style, which comprises the following steps: zooming the purple sand teapot bottom style image, extractingthe key points of purple sand teapot bottom style image under different scale spaces; scaling the purple sand teapot bottom style image; from the extracted key points, a number of key points existingin different scales being selected as stable points adaptively; calculating the matching ratio of the stable points of the two bottoms of the purple sand teapot, and judging the similarity of the twobottoms of the purple sand teapot according to the matching ratio, so as to judge the authenticity of the purple sand teapot.

The invention discloses a polarization SAR classification method based on a deep convolutional bidirectional LSTM twin network, which mainly solves the problem of low classification accuracy caused by fewer polarization SAR data label samples in the existing method. The implementation steps are: 1) input the polarimetric SAR image to be classified and its real object mark, and perform Lee filtering; 2) extract the time series feature vector from the filtered data and divide the training set and test set; 3) the training set 4) Build a deep convolutional bidirectional LSTM twin network and use the training set and sample pair training set to train it; 5) Use the trained network to classify the test set samples to obtain the ground truth object category. The present invention expands the training set and extracts differentiated features under the twin architecture, and makes more reasonable and full use of spatial neighborhood information for bidirectional time-series modeling under the condition of small-sample labeling, so that the classification accuracy of the model is greatly improved.