54results about How to "Improve interpretation" patented technology

The invention provides a method and an arrangement for filtering or pre-processing most any type of multivariate data exemplified by NIR or NMR spectra measured on samples in order to remove systematic noise such as base-line variation and multiplicative scatter effects. This is accomplished by differentiating the spectra to first or second derivatives, by Multiplicative Signal Correction (MSC), or by similar filtering methods. The pre-processing may, however, also remove information from the spectra, as well as other multiple measurement arrays, regarding (Y) (the response variables). Provided is a variant of PLS that can be used to achieve a signal correction that is as close to orthogonal as possible to a given (y) vector or (Y) matrix. Hence, ensuring that the signal correction removes as little information as possible regarding (Y). A filter according to the present invention is named Orthogonal Partial Least Squares (OPLS).

The invention relates to a maneuvering target high-resolution ISAR sub-aperture fusion imaging method. The method includes the following steps: S1. a radar transmits a chirp signal and receives echo data in a dechirping mode; S2. Translation compensation is performed on the echo data, dividing the echo data in a large-angle observation form into a plurality of pieces of sub-aperture echo data; or existing sub-angles having a plurality of angles of view/a multi-base ISARs are used as sub-aperture echo data; S3. Target rotation parameters are estimated based on an image sharpening degree maximization method, and the azimuth resolution of each sub-aperture image is estimated; S4. a sparse signal processing method is utilized to correct the resolution of each sub-aperture image; and S5. geometric registration and fusion are performed on each sub-aperture image, thereby realizing high-resolution ISAR sub-aperture fusion imaging. The maneuvering target high-resolution ISAR sub-aperture fusion imaging method provided by the invention can solve the problem of poor imaging quality caused by target maneuverability under the circumstance of a large angle, multiple angles of view or a multi-base ISAR, and improves capabilities of identifying and explaining unknown target ISAR imaging.

In the computed-based analysis of forming processes, for example, manufacturing sheet metal parts for the automobile industry, the material loading is represented by major and minor strains ε_I, ε_II and is visualised with respect to a forming limit strain curve. In the method according to the invention, one proceeds from a target state (4n) of the material, as has been determined in the computed simulation of the forming process. A proportional trajectory of a loading and thus of the state variables of the material, in particular of the stresses (σ), is determined, which leads to the same target state. The associated proportional strain trajectory is evaluated for this proportional loading trajectory. The strain state (4p) which results from this strain trajectory, is called the equivalent strain state (4p) and may be used in the forming limit strain diagram for assessing the target state. Thereby, the equivalent strain state is set in relation to the forming limit strain curve (1) for the proportional trajectories.

The invention discloses a near infrared spectrum information extraction method based on canonical correlation coefficients. The method comprises the steps that 1, original near infrared spectra and chemical values of tobacco leaves are acquired; 2, the abnormal spectra in the original near infrared spectra and the abnormal values in the chemical values are eliminated; 3, the near infrared spectrum is partitioned into a plurality of spectrum sections, and canonical correlation analysis is conducted on the near infrared spectrum and the chemical value in each spectrum section to calculate the canonical correlation coefficients; 4, a threshold value is selected, and PLS modeling is conducted on the wavelength points where the canonical correlation coefficients are larger than the threshold value. According to the near infrared spectrum information extraction method based on the canonical correlation coefficients, the explanation capacity of the near infrared spectrum can be improved, the multicollinearity of near infrared spectrum information can be eliminated, and the stability of predicting a chemical component model through the near infrared spectrum can be improved.

An apparatus, system, and method are disclosed for merger and acquisition analysis. A survey module may provide a survey regarding organizational aspects, including both subjective aspects and objective aspects. A database module may gather responses to the survey regarding a first company and a second company that are merger candidates into a database of survey data. A reporting module may display a graphic that presents a visual summary of the survey data for each organizational aspect. A recommendation module may generate action recommendations to address root causes of impacts regarding the merger based upon the survey data in the database. The visual summaries may be arranged in a pictorial representation of an interrelationship between the organizational aspects that may be interactively selectable by a user.

A system for heart performance characterization and abnormality detection includes an interface for receiving sampled data representing an electrical signal indicating electrical activity of a patient heart over multiple heart beat cycles and for receiving a pace signal indicating occurrence of a heart pace pulse applied to the heart. A signal processor uses the received sampled data and pace signal in calculating, a first signal characteristic value comprising a time interval between occurrence of the pace pulse and a cardiac cycle characteristic and a second signal characteristic comprising an average of the time intervals determined over a multiple heart cycles. A comparator compares at least one of the first and second characteristic values with a threshold value to provide a comparison indicator. A patient monitor generates an alert message associated with the threshold in response to the comparison indicator indicating a calculated signal characteristic value exceeds the threshold value.

The invention provides a method for detecting sheep FecB gene polymorphism by using a micro-fluidic SNP chip. The method is capable of detecting loci A and G at high throughput and the result is accurate. Compared with other methods for high throughput detection of an FecB gene by using a Taqman MGB probe, the method provided by the invention has the advantages that samples capable of being detected every time are relatively flexible in quantity, the consumption of a reagent is low and the cost is significantly reduced. Nucleotide sequences of used primer and probe are as shown in SEQ ID NO.1-4, so that the specificity is high, the interference of other genes is avoided, the false positive risk caused by PCR product pollution is reduced and result interpretation is relatively intuitive. High throughput detection on the SNP loci of the FecB gene can be achieved, and the method has potential application value in large-scale molecular breeding of sheep.

The invention provides a well-to-well tracing curve clustering method and device. The method includes the steps that after standardization treatment, curve piecewise linearization treatment, non-dimensional tracing-curve-to-tracing-curve form distance calculation and automatic well-to-well non-dimensional tracing curve clustering algorithm treatment are conducted on testing data, automatic well-to-well tracing curve clustering calculation and analysis are achieved, and finally analysis of newly-tested tracing curves is achieved. On the basis of the method, the invention further provides the well-to-well tracing curve clustering device corresponding to the method, standardization treatment is conducted on the complex tracing curves, and scientific and quick analysis of mass well-to-well tracing curves is achieved, so that a specific technological means for classification research on the mass well-to-well tracing curves is provided, and the explanation level of the well-to-well tracing curves is increased.

The invention discloses a target characteristic extraction method, identification method, extraction device and identification system for a synthetic aperture sonar image. The target characteristic extraction method includes the steps of extracting shadow geometrical characteristics which include the target shadow zone area, the perimeter zone contour length, the eccentricity ratio, shape parameters, direction values and the ratio of the largest width of a target to the largest width of a shadow, obtaining a characteristic space formed by the shadow geometrical characteristics, extracting the target normalization central moment, obtaining a characteristic space formed by the target normalization central moment, extracting statistical property parameter difference characteristics of a background, the target and the shadow, obtaining shape parameters and dimension parameters, then obtaining a characteristic space formed based on the statistical property parameter difference characteristics of the background, the target and the shadow, and forming a new characteristic space formed by the three characteristic spaces. According to the target characteristic extraction method and identification method for the synthetic aperture sonar image, an underwater object can be effectively represented, and detection and identification of the synthetic aperture sonar image are facilitated.

The present invention provides methods for individualizing chemotherapy, and particularly methods for individualizing neoadjuvant chemotherapy. The present invention provides methods for predicting a cancer patient's response to neoadjuvant chemotherapy, including assessing the probability of a positive response upon treatment with candidate agents prior to surgery. In various aspects, the invention involves culturing a monolayer of malignant cells from an explant of a patient's biopsy specimen, such as a transcutaneous biopsy-sized specimen, and testing the malignant cells for resistance or sensitivity to one or a plurality of candidate agents for neoadjuvant therapy. In other aspects, the invention provides methods for accurately scoring and interpreting such assays, and discloses in vitro chemoresponse results that are predictive of a patient's pathological complete response (pCR) upon receiving the corresponding treatment regimen.

The invention discloses an insulator pollution component identification method based on a microscopic hyperspectral technology, and belongs to the technical field of power transmission and transformation equipment operation state maintenance. The method comprises the steps of: obtaining a microscopic hyperspectral image of pollution samples of a pollution accumulation insulator, and dividing the microscopic hyperspectral image into a first map set and a second map set; respectively extracting hyperspectral spectral lines of mixed components of the pollution samples in the first map set and the second map set; separating the pollution components of the pollution samples, performing microscopic hyperspectral imaging on each pollution component, and establishing a pollution component spectrum library; establishing a pollution component identification model based on the pollution component spectrum library and the hyperspectral spectral lines of the pollution sample mixed components corresponding to the first map set, taking the hyperspectral spectral lines of the pollution sample mixed components corresponding to the second map set as a test set, and inputting the test set into the pollution component identification model for optimization. The method achieves microscopic detection of the insulator pollution components, is simple in operation process, is beneficial to identification of the pollution components, and can observe the distribution of the pollution components on the surface of the insulator.

The invention discloses a side-scan sonar image gray scale equalization method and system. The method comprises the following steps: geocoding track line data and a side-scan sonar waterfall plot to obtain a side-scan sonar image; dividing each side-scan sonar survey line image with geographic coordinates in the side-scan sonar images into a plurality of path buffer areas, wherein the pixel pointslocated in the same path buffer area are located on the same side of the track line, and the distance between the pixel points and the track line is within a preset range; extracting gray scale features of each path buffer area, and performing gray scale equalization on pixel points in the path buffer areas according to the gray scale features; and performing gap interpolation and image inlayingon all the equalized side-scan sonar survey line images with the geographic coordinates to obtain an equalized side-scan sonar image. According to the invention, gray scale equalization processing iscarried out on the side-scan sonar image after geocoding, the imaging quality of the side-scan sonar can be improved, and the subsequent image interpretation or automatic classification precision is further improved.

The invention provides a semantic association character recognition method and device, and relates to the technical field of image processing. The method comprises the following steps: acquiring a to-be-recognized image, and acquiring a character template corresponding to the to-be-recognized image; calculating the similarity between the to-be-recognized image and the character template; according to the similarity, determining whether the character in the to-be-recognized image is a pre-determined character category, and when the similarity is greater than a preset value, determining that the character in the to-be-recognized image is a target character; dividing an area where the target character is located into a plurality of blocks; checking the characters in each block according to the semantic relevance to obtain a checking result; and identifying the target character according to the inspection result. The characters in the image are accurately recognized through multi-region relevance detection, so that the accuracy of character recognition is improved.

The current invention minimizes the energy losses by pointing the geophone's internal system, which consists of a magnet bar, coil, and springs, towards signals reflected from targets.

The invention provides a three-phase alternating current voltage drop state judgment method and system. The judgment method comprises the steps that sampling voltage is converted from a three-phase stationary coordinate system to a two-phase rotating coordinate system; in the two-phase rotating coordinate system, a d-axis direct current voltage component Ud and a q-axis direct current voltage component Uq are decoupled and separated; and the d-axis direct current voltage component Ud and the q-axis direct current voltage component Uq are filtered to acquire a d-axis direct current voltage component Ud flt and a q-axis direct current voltage component Uq flt, and the d-axis direct current voltage component Ud flt and the q-axis direct current voltage component Uq flt are used to judge whether the power grid voltage drops. According to the invention, the system is rapidly controlled and protected by improving the rapidity and accuracy of the system to judge the states of voltage drop and recovery.

The invention discloses a novel chemical process quality prediction method, comprising the following steps: step 1, collecting sensor data in the chemical process, processing and establishing a novelprocess prediction model; Step 2: Collecting the newly obtained data during the chemical process operation, and using the prediction model obtained in step 1 to carry out on-line prediction. First, the orthogonal signal correction algorithm is used to deal with the historical data collected from the process, and then the prediction model is established by using the processed data. In order to improve the ability of the model to deal with nonlinear data, support vector machine is introduced into the prediction model. This method improves the disadvantage of the traditional prediction model thatthe modeling process is complex and can not deal with the nonlinear data, and improves the ability of the model to track the real data.