612 results about "Statistical significance" patented technology

Various exemplary systems and methods for linking entity references and identifying associations are presented. In particular, a method is provided for linking a plurality of entity references to at least one entity. The method comprises the steps of evaluating a probability of a match between a first entity reference and a second entity reference based at least in part on a statistical significance of one or more field values being common to both the first entity reference and the second entity reference, wherein field value statistical significance is inversely related to a number of field value occurrences occurring in some or all of the plurality of entity references and linking the first entity reference with the second entity reference when the probability is greater than or equal to a match threshold.

Methods for deriving a brand sentiment are presented. Phrases and ratings associated with the brand are stored in a database. The phrases are analyzed and compared to each other and to the ratings to derive a statistical significance of a phrase usage relative to other phrases. A sentiment score is derive from the statistical significance.

A system and method for determining the significance of association rules which are mined from a dataset is provided. Predictive association rules may also be generated based on the significance of an association rule. The statistical significance of an association rule may be used to estimate the number of false discoveries in a dataset or to rank discovered association rules by statistical significance to permit the user of the system to view the most statistically significant association rules first.

A method and apparatus for identifying a speaker within a captured audio signal from a collection of known speakers. The method and apparatus receive or generate voice representations for each known speakers and tag the representations according to meta data related to the known speaker or to the voice. The representations are grouped into one or more groups according to the indices. When a voice to be recognized is introduced, characteristics are determined according to which the groups are prioritized, so that the representations participating only in part of the groups are matched against the o voice to be identified, thus reducing identification time and improving the statistical significance.

System and method of continuously analyzing trial data of an ongoing clinical trial is provided. A statistical analysis is performed on a trial database containing subject trial data. If the result of the statistical analysis does not exceed a predetermined threshold value, then the statistical analysis is repeated while the clinical trial is ongoing. In a blinded clinical trial, a grouped database is generated from the trial database and a blinding database prior to performing the statistical analysis. The grouped database groups the subject trial data according to the study groups. The ability to continuously monitor and analyze the trial data for statistical significance in tandem with data collection while the trial is ongoing provides many benefits to the researchers because the trial database no longer becomes the bottleneck in obtaining useful results and statistical analysis can be conducted on a near real-time basis without having to wait until completion of the trial.

There are provided methods and systems for inferring a user's interests from user-generated tags of web-based content. In accordance with the invention, user-generated tags from viewing web-based content are collected over a predetermined period of time. A subset of distinct or unique tags is identified from among the collected tags. A z-score is calculated for each identified distinct tag, where the z-score is a measure of the statistical significance of the tag. The subset of distinct tags is then sorted based on their corresponding z-score. All distinct tags having a corresponding z-score lower than a predetermined threshold are rejected and the remaining distinct tags, having a corresponding z-score higher than the threshold are used to infer a user's interest. The ability to infer a user's interests from the remaining distinct tags may thus benefit web-based applications by achieving a high degree of accuracy in predicting the interests of users by leveraging on the use of the user generated content tags and keywords.

A method and apparatus for identifying a speaker within a captured audio signal from a collection of known speakers. The method and apparatus receive or generate voice representations for each known speakers and tag the representations according to meta data related to the known speaker or to the voice. The representations are grouped into one or more groups according to the indices. When a voice to be recognized is introduced, characteristics are determined according to which the groups are prioritized, so that the representations participating only in part of the groups are matched against the voice to be identified, thus reducing identification time and improving the statistical significance.

For each of a number of network performance metrics, an associated value rpm that represents a difference between a first correlation coefficient r1 computed for a baseline data set and a second correlation coefficient r2 computed for a second data set that includes the baseline data set and other data points classified as duration outliers is computed. The first and second correlation coefficients for each network performance metric represent correlation between that network performance metric and durations of network connections. The network performance metric that has a largest associated rpm value of all statistically significant rpm values computed is selected as representing the probable root cause of the duration outliers. Statistical significance is measured through comparison of an rpm value with a statistical property of a set of Bayesian correlation coefficients computed for each performance metric.

Systems and methods for determining whether the data for a growth curve represents or exhibits valid or significant growth. A data set representing a sigmoid or growth-type curve, such as a PCR curve, is processed to determine whether the data exhibits significant or valid growth. A first or a second degree polynomial curve that fits the data is determined, and a statistical significance value for the curve fit is determined. If the significance value exceeds a significance threshold, the data is considered to not represent significant or valid growth. If the data does not represent significant or valid growth, the data set may be discarded. If the significance value does not exceed the significance threshold, the data is considered to represent significant or valid growth. If the data set is determined to represent valid growth, the data is further processed to determine a transition value in the sigmoid or growth curve, such as the end of the baseline region or the elbow value or Ct value of a PCR amplification curve.

Detecting fraud in the health care industry includes selecting a given focus scenario (e.g., prescription rate in a certain drug therapeutic class) for audit analysis, and constructing baseline models with the appropriate normalizations to describe the expected behavior within the focus area. These baseline models are then used, in conjunction with statistical hypothesis testing, to identify entities whose behavior diverges significantly from their expected behavior according to the baseline models. A Likelihood Ratio (LR) score over the relevant claims with respect to the baseline model is obtained for each entity, and the p-value significance of this score is evaluated to ensure that the abnormal behavior can be identified at the specified level of statistical significance. The approach may be used as part of a preliminary computer-aided audit process in which the relevant entities with the abnormal behavior are identified with high selectivity for a subsequent human-intensive audit investigation.

The invention discloses a device for classifying dynamic electrocardio data. The device comprises an electrocardio data collecting device, an electrocardio information database, an electrocardio index obtaining device, an electrocardio index screening device, a feature combination obtaining device, a classifier screening device and a classification result output device, wherein the electrocardio index screening device is used for carrying out difference analysis on electrocardio indexes to screen out electrocardio indexes with significance differences, the feature combination obtaining device is used for carrying out feature combination on at least two items in the electrocardio indexes, with the significance differences, screened by the electrocardio index screening device to obtain a plurality of feature combinations, the classifier screening device adopts a plurality of classifiers for testing the feature combinations obtained by the feature combination obtaining device so as to screen out the optimum classifier and the optimum feature combination, the classification result output device is used for receiving the personnel information of patients and pathological data relevant to the heart activity state, classifying the pathological data, relevant to the heart activities, of the patients according to the optimum feature combination and the optimum classifier screened out by the classifier screening device, and outputting the classification results.

The invention discloses a stomach cancer prognostic marker screening and classifying method based on a gene expression profile. The stomach cancer prognostic marker screening and classifying method comprises that a gene the expression of which is changed is screened out from data of the gene expression profile Cox proportional hazard model analysis is established aiming at the screened gene, a gene which has statistical significance is selected as a seed gene, a maximum likelihood model is constructed by means of clinical follow-up information data of the patient to screen out prognosis key genes, then the risk coefficient of each prognosis key gene in the patient is calculated, classification and statistic verification are carried out in dependence on the number of prognosis key genes of the patient, and an optimal classification mode is selected. According to the invention, dimensionality of high-dimension miscellaneous gene expression profile data can be effectively reduced, several key genes which can be applied to clinical detection easily are screened out from tens of thousands of genes, survival and the recurrence risk of the patient are predicted by means of the expression case of the several key genes.

The invention relates to a visual saliency detection method with fusion of region color and HoG (histogram of oriented gradient) features. At present, the existing method is generally based on a pure calculation model of the region color feature and is insensitive to salient difference of texture. The method disclosed by the invention comprises the following steps of: firstly calculating a color saliency value of each pixel by analyzing color contrast and distribution feature of a superpixel region on a CIELAB (CIE 1976 L*, a*, b*) space color component diagram of an original image; then extracting an HoG-based local rectangular region texture feature on an RGB (red, green and blue) space color component diagram of the original image, and calculating a texture saliency value of each pixel by analyzing texture contrast and distribution feature of a local rectangular region; and finally fusing the color saliency value and the texture saliency value of each pixel into a final saliency value of the pixel by adopting a secondary non-linear fusion method. According to the method disclosed by the invention, a full-resolution saliency image which is in line with sense of sight of human eyes can be obtained, and the distinguishing capability against a saliency object is further stronger.

The invention discloses a preparation method of a dendrobium officinale extract. The method comprises the following steps: by taking fresh dendrobium officinale strips as a raw material, performing fermentation with neutral protease after juice squeezing; quickly freezing fermentation liquor, naturally unfreezing the fermentation liquor, and removing starch and other impurities from the fermentation liquor; removing a starch solution through treatment with strongly acidic cation exchange resin and weakly basic anion exchange resin; and finally performing concentration with a titanium stick filter, performing alcohol precipitation and centrifugation, collecting supernatant, and freeze-drying the supernatant to prepare the dendrobium officinale extract. The preparation method is simple to operate, low in cost and high in industrialization degree. The dendrobium officinale extract provided by the invention is used for preparing medicines for treating wounds. Compared with a control group, the dendrobium officinale extract is remarkably different in wound size, healing speed and mean healing time within 10 days after operation of rabbits; and the dendrobium officinale extract can speed up the healing of a wound of a wound model rabbit.

The invention discloses a composition for separating a mononuclear cell and a compound lymphocyte separation medium. All raw materials in a formula of the compound lymphocyte separation medium respectively meet the standard of intravenous injection-grade bulk drugs and are high in safety; the purity of the recovered lymphocyte and the recovery rate of the lymphocyte have no remarkable difference from those of a conventional separation medium control group; and the lymphocyte obtained by separating respectively has equivalent effects to those of the control group in four indexes, namely multiplication, morphology, a surface marker and cytotoxicity activity, and is favorable in clinical application prospect.

The invention discloses a method for determining the quality of an iris image based on machine learning. The method comprises the following steps of: pre-processing the iris image; extracting quality factors of the iris image; fitting probability density functions of positive and negative samples of single quality factors by using multiple Gaussian models; performing fusion by using an improved Neyman-Pearson method to acquire the quality score of the iris image; and determining an optimal quality level by a hypothesis testing method. The invention provides a robust detecting method aiming at defocusing, motion blur and heterotropia; and multiple quality factors are fused by introducing the Neyman-Pearson method to form the quality score, and the image quality level with statistical significance is acquired by the hypothesis testing method. The method can be used for quality determination when the iris image is acquired and performance prediction aiming at a recognition algorithm.

The invention provides an infrared video aerial weak moving target detecting and tracking method. According to the method, a rapid and accurate skyline judgment strategy is provided, a sky scene areais obtained through perception, and under the guidance of a sky scene area perception result, an aerial potential target is obtained from airspace detection through the significance difference betweena target and a background, so that it is ensured that a real target is not missed. A target motion trend is introduced, multi-target similarity comprehensive evaluation is introduced to remove falsealarm interference, and background motion compensation is combined to further confirm a moving target, thereby solving the problem of accurate tracking of the moving target. Experimental results showthat the method is good in robustness, and accurate and steady tracking can be carried out under the complex conditions that the target is shielded, overlapped and disappeared, background changes andthe target is ignored and darkened.

The invention relates to a method for preparing vitamin A microcapsule flour nourishment reinforcer, wherein it uses vitamin A oil as corn, uses HI-CAP100 as wall material, uses O / W high-pressure to emulsify and eccentric atomization technique, to prepare the microcapsule with stable property and flow property. The efficiency of said microcapsule is 99.06%, the yield is 97.81%; with high-pressure liquid test, the vitamin A content is higher than 3.5*105IU / g, the average particle diameter is 85.6 mum; and its bulk specific gravity is not significant different from the bulk specific gravity of flour (P>0.05, stop angle (phi)<=30degree).

A system and method for providing cost-benefit analysis for treatment of a chronic disease such as cancer. The system enables a user to provide input parameters related to a patient, and performs statistical and computational analysis of case histories of other patients and retrospective data related to one or more disease treatment protocols to generate a set of output parameters (potential outcome of the treatment protocols) along with their statistical significance and probability. In addition, the system estimates the cost associated with the treatment protocols using cost related information available for tests, procedures, surgeries, etc., to be performed in a treatment protocol. The average cost and the set of output parameters are displayed to the user which helps in performing the cost-benefit analysis.

The invention relates to a method for the molecular diagnosis of prostate cancer, comprising the in vitro analysis of the overexpression or underexpression of combinations of genes that can distinguish, with high statistical significance, tumorous prostate samples from non-tumorous prostate samples. The invention also relates to a kit for the molecular diagnosis of prostate cancer, which can perform the above-mentioned detection.

The general problem of pattern change discovery between high-dimensional data sets is addressed by considering the notion of the principal angles between the subspaces is introduced to measure the subspace difference between two high-dimensional data sets. Current methods either mainly focus on magnitude change detection of low-dimensional data sets or are under supervised frameworks. Principal angles bear a property to isolate subspace change from the magnitude change. To address the challenge of directly computing the principal angles, matrix factorization is used to serve as a statistical framework and develop the principle of the dominant subspace mapping to transfer the principal angle based detection to a matrix factorization problem. Matrix factorization can be naturally embedded into the likelihood ratio test based on the linear models. The method may be unsupervised and addresses the statistical significance of the pattern changes between high-dimensional data sets.

The invention is suitable for human body target re-identification among multiple cameras in an overlap-free area, and provides a human body target re-identification method among multiple cameras. The method comprises the following steps: A) dividing a known human body image sequence and an individual image sequence to be identified in a map depot into a plurality of groups, and calculating the individual similarity difference characteristics of each group according to prototype similarity characteristics; B) according to the individual similarity difference characteristics of each group and the corresponding tag of the individual similarity difference characteristics of each group, carrying out classifier training; and C) calculating the output weight average value of the classifier so as to determine the human body which is matched to a highest degree. The method can use multiple frames of image data to realize the human body re-identification and measure the similarity of a human body target in the multiple frames of image data. Compared with an algorithm provided by the prior art, a significant difference distance provided by the invention is higher in an identification rate on a data set, and the robustness of influence factors, including large size, dimension, shielding and the like, generated on the human body in a sample image among different cameras can be effectively improved so as to improve the identification rate of the algorithm.

The invention discloses a vibrio qinghaiensis Q67 based long-term microplate toxicity analyzing method of environmental pollutants. The long-term microplate toxicity analyzing method is established by using the vibrio qinghaiensis Q67 as a tested organism and introducing time factors into the toxicity concentration-effect relationship of the traditional compound on the basis of a microplate toxicity analyzing method. The vibrio qinghaiensis Q67 based long-term microplate toxicity analyzing method of the environmental pollutants is characterized by adopting a specific microplate design and sampling scheme and a microplate culture medium suitable for the growth of the vibrio qinghaiensis Q67, measuring the long-term toxicity effect of the environmental pollutants on the vibrio qinghaiensis Q67 and repeatedly measures the toxicity of the same pollutant through multiple plates to ensure the statistical significance of an experimental result. By measuring the long-term toxicity of a part of the environmental pollutants on the vibrio qinghaiensis Q67, compared with short-term toxicity, the long-term toxicity of the tested environmental pollutants is discovered to be obviously higher than the short-term toxicity of the tested environmental pollutants, wherein the difference of the long-term toxicity and the short-term toxicity of antibiotics is most significant. The invention can actually reflect the toxicity of a site compound having specific action on compounds and more reasonably evaluate the toxicity of the pollutants.

The invention provides a high-yield low-pollution preparation method for minced fish products, which belongs to the technical field of aquatic food processing. A main preparation process of the method comprises the steps of removing offal, heads and tails of silver carps, grass carp and other freshwater fishes and obtaining minced fish products through fish collection, rinsing, seasoning, mincing, molding and heating. Aiming at the problems of severe protein loss, low product yield, high content of soluble protein and high COD in rinsing wastewater, and the like in the conventional water rinsing process, the method adopts a novel control acid-base rinsing method, precipitates protein at isoelectric points, and then further recover the protein in wastewater through ultrafiltration membrane, so that the minced fish products prepared have the characteristics of high protein content, high production yield, low environmental pollution and the like. In addition, compared with the products of the conventional water rinsing method, the products of the invention have no significant difference in color, texture, gel properties, sensory property, flavor, storage stability and other characters.

The invention provides a seat comfort objective parameter evaluation method. The seat comfort objective parameter evaluation method is characterized by comprising the following steps of measuring and collecting objective parameters of pressure, angle, myoelectricity, temperature and humidity, enabling a subject to change the leaning and pitching angle periodically on a seat, setting a unified time axis, and guaranteeing to synchronously collect the changes of the objective parameters on the unified time axis; processing the collected object parameter changes, then using data analyzing software under the unified time axis to pair the objective parameter changes and detect a sample t, and obtaining the correlation among the objective parameters and the obvious differences between the leaning and pitching angle of the human body and the objective parameters, and among the objective parameters through analysis; and analyzing the results and obtaining an evaluation conclusion based on the human body data of the subject and human body comfort standard parameters serving as the objective evaluation indexes of the comfort of the seat.

A liquid-based cell preservation liquid composite is characterized by comprising the following components in percentage by weight: cell fixing agent: 2-15% of formaldehyde, preservative: 0.1-5% of sodium diacetate, anticoagulant: 2-10% of sodium citrate, buffering agent: 0.5-2% of sodium chloride, chelating agent: 0.002-0.5% of ethylene diamine tetraacetic acid (EDTA), hemolytic agent: 0.5-10% ofglacial acetic acid, and water: 5-80% of pure water, wherein the formaldehyde is the analytical reagent, and accounts for 37-40%; the sodium diacetate is the food additives; the sodium citrate and the sodium chloride are analytical reagents, and NaCl is more than 99.5%; and the EDTA and the glacial acetic acid are analytical reagents, and H2COOH is more than 99.5%. The invention has the advantages that the liquid-based cell preservation liquid composite can keep the cell form to the maximum extent, can improve the diagnosis accuracy and can prevent the cell form of a specimen from significantdifference at room temperature for at least three months.

The invention discloses a method for aided identification of fat tail properties of sheep and a special molecular marker used therein. The invention provides the method used for aided identification of fat tail properties of a to-be-detected sheep colony. The method comprises the following steps: (1) randomly drawing a to-be-detected sample with statistical significance from the to-be-detected sheep colony; (2) detecting the T / C ratio of site 59383635 of an X chromosome of the to-be-detected sample; and (3) carrying out evaluation according to the standards that the to-be-detected sheep colony is a fat rump type colony if the T / C ratio is greater than 5, the to-be-detected sheep colony is a slim tail type colony if the T / C ratio is smaller than 0.5 and the to-be-detected sheep colony is a short fat tail type colony if the T / C ratio is in a range of 1 to 2. Experimental results of the invention show that distribution of the site 59383635 of the X chromosome of sheep in a fat tail (rump) type sheep colony and a slim tail type sheep colony is greatly different and the SNP site can be used as an ideal molecular marker for breeding of a low fat sheep variety.

The invention discloses an improved immune fluorescyte staining method, comprising 5 steps: fixing / permeating, permeating, surface staining, staining in nucleus, washing and weight dropping; the method of the invention is an improvement to the Foxp3 immune fluorescyte staining method of eBioscience Company, changes a two-step multiple staining method into a one-step multiple staining method, and carries out the staining on the surface of the cell and in the nucleus simultaneously, thus having the advantages of simple and convenient operation, quick staining, saving reagent, and reducing the cost, etc. The research shows that the method of the invention has no remarkable difference with the method of that of the eBioscience Company, can be used for the staining on the surface of the cell and in the nucleus simultaneously and has extremely good application prospect and promotional value.

A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

The embodiment of the invention provides a determination method and system of an equipment threshold value. The method comprises the following steps: obtaining a data sample of the equipment, wherein the equipment is from the same totality; judging whether the data sample complies with normal distribution or not, and if the data sample complies with the normal distribution, determining an expectation and standard difference of the data sample; and according to the expectation and standard difference of the data sample, calculating a significant difference threshold value of the data sample, and taking the significant difference threshold value as the threshold value of the equipment. The threshold value, which is subjected to substantial change, of the equipment is effectively found out, the fault hidden dangers of various pieces of equipment can be removed in time, and the precision and the adaptability of the equipment threshold value can be improved.