115 results about "Correlation factors" patented technology

A method for constructing geo-location service replies (e.g. “You are near Bob's Café”, or “Proceed one block north to Bob's Café”) based on landmark-related relevance factors (e.g. if the user's location is close to a known landmark or sponsored location) to serve to a client terminal (e.g. a user's a mobile telephone, a smart phone, a GPS terminal). The system receives a user's geo-location service request (e.g. “Where am I”), and proceeds to construct one or more response candidates to service the user's geo-location service request. Candidate replies are then scored based on relevance factors (e.g. does the candidate location relate to the user's recent geo-service queries, is there a sponsored landmark in general proximity, etc), and high scoring geo-service replies are sent to the user's client terminal. In some cases, more than one relevance factor is considered (e.g. proximity relevance, visibility relevance, familiarity relevance, etc).

Disclosed are ultrasound devices and methods for use in guiding a subdermal probe during a medical procedure. A device can be utilized to guide a probe through the probe guide to a subdermal site. In addition, a device can include a detector in communication with a processor. The detector can recognize the location of a target associated with the probe. The processor can utilize the data from the detector and create an image of a virtual probe that can accurately portray the location of the actual probe on a sonogram of a subdermal area. In addition, disclosed systems can include a set of correlation factors in the processor instructions. As such, the virtual probe image can be correlated with the location of the actual probe.

The present invention is a method and system for continuously monitoring cardiac output. In a preferred embodiment, the method and system of the present invention comprises a pneumotachograph, differential pressure transducer, and a signal amplifier / conditioner interconnected to a programmed digital computer. A patient, preferably, inserts the pneumotachograph in his mouth or, alternatively, the pneumotachograph is connected to a patient's tracheal cannula. As the patient exhales and inhales the differential pressure transducer measures the drop in pressure as air flows through the pneumotachograph thereby producing a weak electrical signal non-linearly proportional to flow. Next, the weak signal is directed through the amplifier / signal conditioner which increases the amplitude and removes some of the noise contained in the transducer output. A digital computer is then utilized to convert the analog time varying electrical signal into a stream of digital data, store it on disk, display it in real time and processes the signal using an experimentally determined correlation factor and mathematical equations relating the fluctuations in air flow with stroke volume to obtain the cardiac output.

The invention discloses a patient portrait drawing method and device based on medical big data. A professional medical clinic knowledge base is established, a new calculation model and a new method are adopted on the basis to construct a patient label, and the problems that universal user portrait drawing is low in accuracy and is not suitable to apply in the medical field and the individual privacy of the patient is difficult in protection are solved. In the method and the device, the extraction and the calculation of a label system are established on the basis of a medical knowledge base so that the method and device exhibit strong speciality, and therefore, the accuracy of the patient portrait drawing system is improved to a great extent; secondly, the risk factor, the increasing-decreasing factor and the correlation factor of label characteristics are considered so that the method and device are more in line with the disease development law; thirdly, the patient participates in the confirmation and the management of portrait drawing so as to eliminate the calculation deviation of the label; and finally, a block chain technology is introduced to the aspect of the individual privacy of patient portrait drawing data, and a risk that sensitive medical data is leaked is technically lowered.

The invention relates to a device and method for monitoring a swimming performance. The device comprises one or more motion-sensitive sensors for providing motion data characteristic to the motion of the swimmer during said swimming performance and a computing unit adapted to detect body motions from said motion data using predefined criteria. According to the invention the computing unit comprises means for calculating a plurality of correlation factors depicting correlation of motion data between successive body motions detected, means for storing the correlation factors as a time series, and means for determining one or more parameters characteristic to the swimming performance based on said correlation factors stored. The invention can be used for robust determination of swimmer's turns, distance swum or swimming style, for example.

A slow cooker having a thermometer such as a capillary thermometer and a graphic display device for indicating a temperature condition of the food product contained within the cooking vessel, the thermometer measuring the temperature of an outer surface of the cooking vessel and the graphic display device displaying the temperature measured by the thermometer but adjusted by a correlation factor to indicate at least an approximate temperature of the food product within the cooking vessel.

Embodiments of the disclosure provide a system for correlating document pages. The system receives a source image of a document page and a rendered image of a markup language page converted from the document page. The system then performs a correlation analysis between the source image and the rendered image. Next, the system determines a correlation factor between the source image and the rendered image based on the correlation analysis, wherein the correlation factor indicates a page fidelity between the document page and the markup language page converted from the document page.

A device for irrigation and / or insufflation during endoscopic surgery / procedures in a body cavity, comprising a first fluid pump device to deliver fluid to the body cvity, a second fluid pump device to move fluid from the body cavity, a control unit connected to the first and / or second fluid pump device, a blood pressure measuring device, wherein the control unit to derives a control signal based on a signal from the blood pressure measuring device, and sends the control signal to the first fluid and / or second fluid pump device, wherein the control signal is derived by processing the signal from the blood pressure measuring device using a correlation factor in the device, dependent on the relationship between a blood pressure measurement signal, and a perfusion pressure of the body cavity, wherein the first and / or second fluid pump device controls the pressure in the body cavity based on the control unit's control signal.

The invention provides a multi-focus image fusion method based on sparse decomposition and a differential image. The multi-focus image fusion method is characterized by comprising the steps of utilizing RPCA to decompose an original image to obtain its sparse component and low-rank component, enhancing an edge of the sparse component through guide filtration, adding the enhanced sparse component to the low-rank component to construct an enhanced image comprising a strong edge, performing differential processing on the enhanced image and the original image, calculating spatial frequency of an obtained differential image, utilizing a self-adaptive threshold algorithm to obtain a spatial frequency diagram of the differential image, utilizing a morphological algorithm to remove a pseudo-focus region in the spatial frequency diagram to obtain a fusion decision-making diagram, and reconstructing a fusion image according to the fusion decision-making diagram and a fusion rule. Three index of the multi-focus image fusion method in evaluating an image fusion algorithm, namely a correlation coefficient, edge gradient information and an edge correlation factor are higher than that of other classical algorithms by more than 45%, 6% and 15% respectively.

The utility model provides a method and the system that sorts blog articles, relating to the field of communication. The method that sorts blog articles comprises building index and sorting inquiry according to the input of users. The method is characterized in that: the steps of building index are as follows: A. correlation factors are extracted from a blog system; B. the correlation weight value of all blog articles and the retrieval terms are calculated according to the correlation factors, and at the same time the blog articles with cheat texts are identified and declined weight; C. the index between all blog articles and the retrieval terms is constructed according to the correlation weight value after weight declination. The utility model identifies and processes blog articles with cheat texts in the calculation of the correlation weight value, thus establishes a correct index and sorts searched blog articles based on the index; therefore, improves the objective accuracy of the sorting and ensures the retrieval quality of the users.

The invention discloses an extraction method for influence factors of carbon exchange of an ecosystem and a system. The extraction method includes steps of 1), acquiring attribute data of carbon flux samples in a carbon flux data observation station; 2), inputting the attribute data, which are obtained in the step 1), of the carbon flux samples, selecting the optimal combination by the aid of proposed fuzzy rough and reduction integrated algorithm of shuffled frog leaping or quick fuzzy rough and reduction integrated algorithm based on importance, and finding an environmental factor set with the closest relationship with carbon flux; and 3), realizing modeling and stimulating for various environmental factors in the environmental factor set obtained from the step 2) by the aid of a neural network, and obtaining extraction rate of the environmental factors of the carbon flux. The extraction system comprises a data import module, a factor extraction module, an input module and an evaluation module. By the aid of the extraction method and the system, the range of correlation factors of the carbon flux in the researched ecosystem can be effectively reduced, research efficiency is improved, and inherent law among the environmental factors is found.

The invention discloses an intelligent operation and maintenance method based on integrated learning photovoltaic prediction, comprising the following steps: S1, preprocessing the historical photovoltaic data of a power station collected by a photovoltaic monitoring cloud platform; S2, pre-processing the historical photovoltaic data of the photovoltaic monitoring cloud platform; S2, analyzing thecharacteristic correlation of the pre-processed data to determine the strong correlation factors affecting the output power of the power generation quantity; 3, establishing a photovoltaic predictionmodel and fitting data; S4, training the photovoltaic prediction model and optimizing the model; 5, embedding a photovoltaic prediction model into a photovoltaic monitoring platform, inputting data inreal time to obtain a prediction value, comparing the prediction value with the actual value, and setting a deviation interval; S6: guiding the operation and maintenance of the power station according to the interval where the deviation value in step S5 is located. The intelligent operation and maintenance method based on the integrated learning photovoltaic prediction provided by the invention predicts the photovoltaic power through the integrated learning algorithm and embeds the photovoltaic prediction model into the photovoltaic monitoring cloud platform, thereby improving the construction quality of the power station, reducing the later operation and maintenance cost of the power station and reducing the artificial input.

A method for combining a random set of video features non-linearly to evaluate perceptual quality of video sequences includes (a) receiving a video sequence for image quality evaluation; (b) providing an objective metric image quality controller comprising a random set of metrics ranging from M1 to Mn without dependency information for each one metric; (c) applying each one metric individually to the video sequence to provide an individual objective scoring value of the video sequence ranging from x1 to xn; (d) determining a plurality of sets of weights (w1 to wn) which correlate to predetermined subjective evaluations of image quality for a predetermined plurality of video sequences (n), each one set of weights being assigned a range having an incremental value equal to the range divided by a number of combinations for each one set of weights; (e) weighting each individual objective scoring value x1 to xn provided by each one metric of the random set of metrics in step (c); (f) combining metrics of the weighted individual objective scoring value of the random set of metrics into a single objective evaluation F, wherein each weighted individual scoring value from step (e) is multiplied by each individual objective scoring value x1 to xn from step (c); (g) calculating a correlation factor R to provide a correlation value for the objective evaluation F and the plurality of video sequences (n). Steps (e), (f) and (g) are repeated to provide a plurality of correlation factors which are ranked. A heuristic search uses a genetic algorithm to find the best set of weights to provide objective scores closest to predetermined subjective evaluations. A system provides the hardware and modules that perform the non-linear combination of metrics to provide enhanced perceptual image information.

A novel and useful apparatus for and method of packet detection and carrier frequency offset estimation. The packet detection mechanism is robust to channels and sustains reasonable miss-detect (and false alarm) rates at low SNR values. The mechanism uses a modified combined cross correlation and delay and correlate scheme. A delay and correlate scheme is used in order to handle the effects of multipath while swapping integration and multiplication to increase cross-correlation factors resulting in improved sensitivity in low SNR conditions. Correlation is divided into multiple chains to generate a plurality of partial correlations to observe short patterns in the spread sequence resulting in improved performance in long multipath channels.

The invention discloses a vision correlation model progressive rendering method on a three-dimensional scene. The main concept is that a vision correlation factor is calculated according to the distance from a view point to a target, LOD rendering is carried out on geometric data and texture data of a model, the rendering process of the model is controlled through an synchronization strategy and a view point correlation sorting algorithm, and therefore the problems that an existing large-scale three-dimensional model is low in rendering speed, occupies too many system resources such as the inner memory and video memory, has too many rendering areas, is unsmooth in rendering, has the phenomenon of visual mutation, is low in efficiency and the like are resolved.

A test quality evaluating and improving system has a fault-layout information link section which creates a weighted fault dictionary by correlating a layout element related to an undetected fault, out of faults corresponding to a specified fault model and occurring in a circuit to be tested, with the undetected fault as a weight of the undetected fault which cannot be detected by a test pattern for testing the faults; a test quality measure calculating section which multiplies the weight of the undetected fault, the failure mode-fault model correlation factor for correlating the failure mode of the layout element and the fault model, and the failure occurrence rate of each layout element, and outputs an obtained product as a failure remaining rate of the test pattern; a determining section; and a test point inserting section.

This invention provides a system and method that improves the sensitivity and localization capabilities of Magnetic Particle Imaging (MPI) by using combinations of time-varying and static magnetic fields. Combinations of magnetic fields can be used to distribute the signals coming from the magnetic particles among the harmonics and other frequencies in specific ways to improve sensitivity and to provide localization information to speed up or improve the signal-to-noise ratio (SNR) of imaging and / or eliminate the need for saturation fields currently used in MPI. In various embodiments, coils can be provided to extend the sub-saturation region in which nanoparticles reside; to provide a static field offset to bring nanoparticles nearer to saturation; to introduce even and odd harmonics that can be observed; and / or to introduce combinations of frequencies for more-defined observation of signals from nanoparticles. Further embodiments provide for reading of the signal produced by cyclically saturated magnetic nanoparticles in a sample so as to provide a measurement of the temperature of those nanoparticles. The spectral distribution of the signal generated provides estimates of the temperature of the nanoparticles. Related factors may also be estimated—binding energies of the nanoparticles, phase changes, bound fraction of the particles or stiffness of the materials in which the nanoparticles are imbedded.

The invention belongs to the technical field of wind speed prediction, and discloses a wind speed prediction method and system based on a neighborhood gate long-short-term memory network. The Pearsoncorrelation coefficient and the maximum information coefficient are respectively adopted to explore the linear and nonlinear correlation among variables to screen the wind speed correlation factors. On the basis of correlation analysis, the Granger causality test is used to explore the statistical causality of wind speed and wind speed factors. The structure of causality is divided into five types, and all types of causality are unified into an equivalent tree causality structure by the method of 'decomposition-dummy variable-pruning'. Aiming at the causality structure of equivalent tree, a long-term and short-term memory network model based on neighborhood gates is proposed to predict wind speed. The prediction method (NLSTM) of the invention accurately considers the causality between thewind speed and the wind speed factors, effectively improves the prediction accuracy of the wind speed, and plays a vital role in the application of the wind power and the dispatching of the power grid.

The invention discloses a method for retrieving service resources on the basis of user interest. The method includes particular steps of acquiring interest information of users and generating interest profiles of the users; representing the interest profiles of the users by binary-group interest vector tables; computing interest correlation factors of correlation documents; extracting question vectors in retrieval requests of the users; analyzing the similarity among the question vectors and document vectors; computing the interest similarity among the documents and the question vectors; sorting the correlation documents according to degrees of the interest similarity. The method has the advantages that the user interest is extracted and analyzed when the service resources are retrieved, so that actual retrieval requirements of the users can be met, the service resources can be retrieved in a personalized manner on the basis of the user interest, a retrieval effect can be obviously improved, the massive network service resource retrieval time can be shortened, and the efficiency can be obviously enhanced.

The invention discloses a method and device for grading a checked person in security check. The method comprises the steps: generating a risk recognition model of the checked person through historicalsecurity check information; obtaining the safety correlation factor information of the current checked person; generating a safety correlation feature set through the safety correlation factor information via data cleaning; and determining the risk level of the current checked person in real time through the safety correlation feature set and the risk recognition model. The method provided by theinvention can improve the security check efficiency, and achieves the differential check of the checked person.

The invention provides a medium-and-long term runoff ensemble forecasting method, and belongs to the field of hydrological forecasting. The method comprises the following steps: firstly, respectivelyacquiring historical runoff data of a forecast object, acquiring historical meteorological data as a local correlation factor, and acquiring climate factor data as a remote correlation factor; takingthe runoff data of the first 11 months of the month to be forecasted as a time sequence autocorrelation factor; selecting the factor with the highest correlation coefficient from all the factors to form a forecasting factor set; and inputting the forecasting factor set data corresponding to the month to be forecasted into the model by utilizing the trained and verified machine learning runoff forecasting model to obtain a forecasting value of the runoff volume of the month. The method can be practically applied to month-by-month runoff calculation of hydrological station data missing regions and station sparse regions, can also be used for interpolation of missing runoff data, and provides an effective reference basis for local water resource distribution and management, especially arid region reservoir scheduling, local irrigation planning, agricultural water management and the like.

A system detecting emerging risks in various systems and relating a detected risk to its relative impact on a system or product. A server receives and stores risk information from geographically distributed computerized data sources via a communication network. The risk information includes an identification and rating of a specific risk, and information associating the specific risk with a geographical area. Utilizing the risk information and area attributes, such as correlation factors and spreading patterns, a specific risk emerging in a first geographical area and spreading to one or more second geographical areas is detected. Emerging risks can be detected in geographical areas for which no risk information has been received, allowing to set up, maintain, and operate a risk detection system with a simplified technical infrastructure since it is not necessary to measure, transmit, and store risk indicators for all geographical areas for which emerging risks are detected.

The invention discloses an MV (minimum variance) wave beam formation and MV-based CF (correlation factor) fusion method. The method comprises the following steps of: constructing an MV constraint matrix by utilizing a direction vector corresponding to a group of maximal value output by a traditional wave beam forming device; acquiring the output of an MV wave beam formation by an MV wave beam forming algorithm, and replacing the correlation part of the CF by the output formed by the MV wave beam so as to form a CF with high resolution; and weighting the correction coefficient with high resolution and the output formed by the MV wave beam, thereby obtaining an output model formed by the wave beam finally. According to the invention, by utilizing the high resolution of MV, the correlation part of CF is replaced by the output formed by the MV wave beam so as to form the CF with high resolution, and the CF with high resolution and the output formed by the MV wave beam are subjected to weighting and fusion; and the simulation result verification of a point scattering target and a sound absorption target shows that compared with the prior art, the method provided by the invention can improve the resolution, contrast and robustness of images well.

The invention relates to a multi-partition clustering preprocessing method of stream data. The method includes the following steps that: the trend factors of the stream data are screened, and a correlation degree is calculated; statistical analysis is performed on the stream data, a low-dimensional database partitioning method is adopted for high-correlation factors in a high-dimensional database, and isometric triangle partitioning is performed on low-correlation factors; a distribution-based partitioning method is adopted for a low-dimensional database; a DBSCAN (density-based spatial clustering of applications with noise) algorithm is adopted to perform clustering in each rule partition; and local clustering results are merged. According to the multi-partition clustering preprocessing method of the stream data of the invention, multi-partition improvement is made for the clustering preprocessing of the stream data, and therefore, data distribution is more uniform, clustering results are more accurate, and distributed parallel processing of the data is realized, and the pressure of low data preprocessing efficiency of a large number of data sequences which arrive sequentially, fast and continuously can be alleviated.

A flavor monitoring system comprises a photo-ionization detector based sensor for measuring the amount of flavor in flavored cigarette filters The sensor has an intake port and an exit port open to the atmosphere. An enclosure with a removable cover is connected to the intake port of the sensor, and the enclosure is constructed and arranged to receive a flavored cigarette filter to be analyzed. The photo-ionization detector based sensor draws a gaseous sample from the flavored filter within the enclosure, ionizes the flavor sample and displays a reading representative of the amount of flavor in the filter. Subsequently the reading may be converted to a flavor amount in milligrams by multiplying the reading by a correlation factor.

The embodiment of the invention discloses a matching detection method and device. The method includes the steps that an audio feature sequence of an audio file and a subtitle feature sequence of a subtitle file are established; according to the audio feature sequence and the subtitle feature sequence, correlation factors are determined; correlation operation is conducted through the correlation factors, and a correlation function sequence is obtained; according to the correlation function sequence, matching detection is conducted on the audio file and the subtitle file. According to the method and device, matching detection can be conducted on the audio file and the subtitle file, the application requirements of the audio file are met, and application intelligence of the audio file is improved.

The present invention provides a chip screening method and apparatus. The method comprises: calculating a first influence factor of each chip within a peripheral range of a to-be-determined chip, and summing the first influence factors of the chips within the peripheral range to obtain a sum of the influence factors; normalizing the first influence factor of each chip within the peripheral range based on the sum of the influence factors to obtain a second influence factor; summing the second influence factors of effective chips within the peripheral range to obtain a correlation factor NDCF of the peripheral chips of the to-be-determined chip; and if the NDCF of the to-be-determined chip meets predefined screening criteria, determining that the to-be-determined chip is a chip with a large potential failure rate. The present invention reduces chip screening costs.

The invention relates to an Argentina squid resource recruitment prediction method, which is characterized in that by using the correlation between a time sequence value formed by marine environment factors of a feeding ground in a feeding month and a CPUE (Catch per Unit Effort) time sequence of the current year, marine environment factors of a sea area with high correlation are selected to act as correlation factors for influences of a feeding and inhabiting environment for Argentina squid resource recruitment; by using the correlation between a time sequence value formed by marine environment factors of a spawning ground in a spawning month and a CPUE time sequence of the next year, marine environment factors of a sea area with high correlation are selected to act as correlation factors for influences of a spawning and inhabiting environment for the resource recruitment; the inhabiting environment appropriateness degrees of the spawning ground and the feeding ground are expressed through the proportion PS and the proportion PF by using the proportion of an appropriate surface water temperature range of the spawning ground in the spawning month to the total area and the proportion of an appropriate surface water temperature range of the feeding ground in the feeding month to the total area; and BP network structure prediction models are built respectively by using different combination of the selected environment factors, the proportion PS and the proportion PF, and an optimal model is selected so as to be used for medium and long term fishing condition forecasting.

The invention provides a resource complementary quantity prediction method of Peru squid. The resource complementary quantity prediction method is characterized in that by use of correlation between a time sequence value formed by marine environment factors of a feeding ground in feeding months and a CPUE time sequence of this year and selecting marine environment factors of a sea area with high correlation as correlation factors of influence on complementary quantity of squid resources by a feeding habitat environment; by use of correlation between a time sequence value formed by marine environment factors of an oviposition month and an oviposition field and a CPUE time sequence of next year, selecting marine environment factors of a sea area with high correlation as correlation factors of influence on complementary quantity of squid resources by an oviposition habitat environment; by use of the proportion of suitable surface water temperature scope of oviposition months and oviposition fields to total area and the proportion of suitable surface water temperature scope of feeding months and feeding fields to total area, using P<s> and P<f> to represent the oviposition field inhabit environment suitable degree and the feeding field inhabit environment suitable degree respectively; and using a selected environment factor and different combinations of the P<s> and P<f>, establishing BP network structure prediction models, and selecting an optimal model. The resource complementary quantity prediction method is used for medium and long term fishery forecast.