89 results about "Statistical mean" patented technology

A computer-implemented method and apparatus for embedding hidden data in an audio signal. An audio signal is received in a base domain and then transformed into a non-base domain, such as cepstrum domain or LP residue domain. The statistical mean manipulation is employed on selected transform coefficients to embed hidden data. The introduced distortion is controlled by psychoacoustic model to ensure the imperceptibility of the embedded hidden data. Scrambling techniques can be plugged in to further increase the security of the data hiding system. The present new audio data hiding scheme provides transparent audio quality, sufficient embedding capacity, and high survivability over a wide range of common signal processing attacks.

A method for evaluating statistical congruence of an existing or putative portfolio with a target portfolio, both the current portfolio and the target portfolio having a plurality of assets. A mean-variance efficient portfolio is computed for a plurality of simulations of input data statistically consistent with an expected return and expected standard deviation of return, and each such portfolio is associated, by means of an index, with a specified portfolio on the mean variance efficient frontier. The number of simulations and the number of simulations periods is specified on the basis of a specified information correlation value. A statistical mean of the index-associated mean-variance efficient portfolios is used for evaluating a portfolio, in accordance with a specified balancing test, for statistical consistency with a specified risk objective and, additionally, for defining investment-relevant allocation ranges of portfolio weights.

The present invention provides methods using a gene expression profiling analysis (1) to determine whether a human sample is a tumor using a gene set containing nucleic acid sequences of SEQ ID NOS: 1-7, 8-17 or 1-17; (2) to identify whether a tumor tissue is an adenocarcinoma (using a gene set containing nucleic acid sequences of SEQ ID NOS: 15, and 18-21) or a squamous cell carcinoma (using a gene set containing nucleic acid sequences of SEQ ID NOS: 22-27); and (3) to predict the prognosis of survival and metastasis in humans with tumor (using a gene set containing nucleic acid sequences of SEQ ID NOS:19, and 28-42 or SEQ ID NOS: 19, 29, 31, 40, and 42), particularly for those humans who are at the early stage of lung cancer. The gene expression profiling is preferably performed by cDNA microarray-based techniques and/or Real-Time Reverse Transcription-Polymerase Chain Reaction (Real-Time RT-PCR), and analyzed by statistical means.

Within the frameworks of hierarchical neural feed-forward architectures for performing real-world 3D invariant object recognition a technique is proposed that shares components like weight-sharing (2), and pooling stages (3, 5) with earlier approaches, but focuses on new methods for determining optimal feature-detecting units in intermediate stages (4) of the hierarchical network. A new approach for training the hierarchical network is proposed which uses statistical means for (incrementally) learning new feature detection stages and significantly reduces the training effort for complex pattern recognition tasks, compared to the prior art. The incremental learning is based on detecting increasingly statistically independent features in higher stages of the processing hierarchy. Since this learning is unsupervised, no teacher signal is necessary and the recognition architecture can be pre-structured for a certain recognition scenario. Only a final classification step must be trained with supervised learning, which reduces significantly the effort for adaptation to a recognition task.

A computer to improve prediction of solar output for a solar power system that includes a processor and a memory. The memory has software code which when executed causes the computer to receive power output data from the solar power system, calculate a statistical mean of the power output data, receive solar hour information from an almanac system and generate an almanac predicted power output for the solar power system for the specified time period. The computer receives weather information for the specified time period from a weather predicting source and calculates a weather prediction-to-solar almanac ratio based on a comparison of the solar hour information to the weather information. The computer generates a predicted power output for the specified time period by multiplying the almanac predicted power output for the solar power system by the weather prediction-to-solar almanac ratio and stores the predicted power output for the specified time period.

Provided is an itinerary working area boundary extraction method based on an aggregation degree and Delaunay triangular reconstruction. The method comprises the steps of defining relevancy of two data points, and conducting equidistant compression on the data points based on an accelerated optimization algorithm of equidistant compression; conducting refined extraction on an area-of-interest boundary. The method specifically comprises the first step of preprocessing the data points; the second step of solving a Delaunay triangular net M for a point set S; the third step of utilizing an alpha-shaped algorithm to solve an edge list of an concave envelope of the point set S. In the coarse extraction stage, the dense distribution character of cruise working points is fully made use of, a concept of aggregation degree calculation is put forward, the equidistant compression algorithm is applied, and the speed of automatic location of a cruise area is effectively increased. In the refined extraction stage, an alpha-shape concave envelope edge solving algorithm based on statistical average information is applied, an unreasonable triangle obtained by Delaunary triangulation is automatically recognized and deleted, it is guaranteed that the method has strong adaptation to different triangular grids, and the accuracy degree of edge extraction is greatly increased.

Methods and apparatuses are provided for detecting and characterizing heterogeneities within a bulk material that exhibit scale-dependent uniformity represented by locally representative volume elements (LRVEs). The invention is particularly useful in the characterization of local variations of crystallographic texture of metals and alloys, including metallurgical Ti alloys. The invention consists of generating ultrasonic waves through different paths in the object, and detecting differences in time, amplitude and/or phase of the detected frequency components traveling the different paths to characterize a statistical mean dimensions of the LRVEs, for example, by autocorrelation. Mean sizes of the LRVEs in the scan directions can be computed by autocorrelation, and mean sizes in the direction of the propagation can also be approximated.

A method for representatively sampling a subsize rock model structural surface sample sampled based on layering probability comprises the following steps of: (1) orientationally counting and measuring fluctuation amplitude of a raw rock structural surface sample, respectively calculating a roughness coefficient characteristic constant JRC and a statistic average value of each measuring segment of the scale by a formula; (2) calculating based on quartile division to obtained JRC average values and variances of three intervals: P0-25, P25-75 and P75-100; and (3) setting a relative permissible error of an average value of samples and an ensemble average value to be gamma, and setting confidence to be 95%. The said calculated data is substituted into a layeredly sampling formula to obtain a total sample size, and the sample size of each layer is determined based on the layer weight: W0-25=1/4, W25-75=1/2 and W75-100=1/4. The method provided by the invention can effectively satisfy statistic precision requirement of the shear strength dimension effect of the rock model structural surface, and can raise test statistic precision.

Methods for separation of two optical isomers in a racemate into its constituent isomers by statistical means are described, whereby the saturated racemate solution is first allotted into small samples by means of microfluidic or inkjet techniques to obtain small sample quantities (picoliters to microliters) with one isomer in measurable excess of the other. The samples are then tested by means of spectrophotometers used for measuring Cotton Effects or Circular Dichroism or other related effects which measure the difference in the absorption of right and left circularly polarized light, so that there is a predetermined minimum excess of one enantiomer. Collecting them in three different receptacles then separates the three types of samples. The right and left excess samples are then used in the crystallization process to obtain right or left handed isomers respectively. The third type of sample that is collected is again re-circulated through the sampling process so that right and left excess samples are collected again out of the neutral samples (with less than minimum excess of one kind or the other) and the process continued to crystallize out the two isomers.

A method is provided for verifying and/or updating map geometry based on a probe data. A method may include: receiving probe data from a plurality of probes within a region, where the probe data includes at least one of heading information and location information for each probe data point; matching the probe data to a link segment to generate map-matched probe data; calculating a difference between the at least one of heading information and location information of the map-matched probe data points and of the link segment; determining a statistical mean of the data; determining an error of the statistical mean of the data; and flagging the link segment for manual review in response to the statistical mean being greater than the error of the statistical mean multiplied by a biasing factor.

An approach for discovery of relevant data in massive datasets. Compare datasets including compare key fields, compare data fields and a core dataset including target data field(s) and core field(s) are received. The compare datasets are categorized into direct and indirect related dataset pools based on the target data field(s) correlation strength with matching compare and core fields. The direct related dataset pool and the core dataset are transformed into reduction datasets based on statistical measure of values of target data fields, shared key fields and compare data fields. Target correlations of the reduction datasets are creating based on a reduction compare and target data fields. Statistical relationship strength of core dataset and the direct related dataset pool are created based on a statistical mean of target correlations and a relevancy data store is created.

The embodiment of the invention discloses a method and a system for determining the load stability state of a thermal power generating unit. The method comprises the steps of obtaining the load data of the thermal power generating unit; storing the load data to a database, working out the standard deviations of the load data according to the load data, counting the standard deviations of the load data, obtaining a standard deviation threshold for distinguishing the load stability state and the load instability state, and determining the load stability state of the thermal power generating unit. According to the method provided by the invention, distinguishing and screening are performed in the historical data by the statistical means, and thereby the stability state and the instability state of the historical loads of the thermal power generating unit are finally distinguished, the start time and stop time of the load stability state of the thermal power generating unit are determined, and a foundation is provided for further exploring the operating characteristics of the thermal power generating unit.

The invention provides a radar signal processing method for detecting a low, slow and small target under a complex clutter background. The method comprises the following steps: performing spectral analysis on a slow time data sequence in each distance unit of a sampled moving target echo pulse sequence to obtain Doppler domain data; carrying out sliding window processing on the Doppler domain dataand acquiring a statistical variance and a statistical mean value in each reference window and a statistical mean value ratio of a front reference window to a rear reference window; judging the uniformity of background clutters in each reference window according to the statistical variance and the statistical mean value; selecting a corresponding constant false alarm detection algorithm accordingto the uniformity of the background clutter to obtain a target trace point in the reference window; and obtaining the speed, pitch, orientation and distance of the target according to the trace pointinformation.

The invention discloses a method for determining mixing time of multiphase flow by using a RGB color model, belonging to the technical field of metallurgical energy engineering. The method determines macroscopic mixing time of multiphase flow on the basis of statistical mean square deviation, average change rate and the RGB color model for image processing and is mainly applied to chemical engineering for determination of the mixing time of multiphase flow and evaluation of mixing effect. The method is simple and convenient, has high practical value and provides a reliable and practical method for evaluation of mixing time of chemical and metallurgical stirring equipment and theoretical guidance of designing of a stirring reactor.

The present subject matter overcomes the deficiencies in the prior art by introducing or generating charged particles in an air stream and manipulating the air stream with magnetic fields operating on the charged particles. Embodiments of the present subject mater compress the air stream by accelerating charged particles with a moving magnetic field, where the magnetic field has a velocity perpendicular to its flux lines. The increased velocity of the charged particles increases the statistical mean particle velocity and thereby increases the pressure in the air stream. The compressed air stream is then heated and expanded through a second magnetic field. The expansion of the air stream substantially increases the velocity of the air stream and the charged particles therein. The interaction of the high velocity charged particles and the magnetic field imparts a force perpendicular to the flux lines, this force powers the movement of the magnetic field and can also be extracted in the form of mechanical work.

According to typical inventive practice, a baseline describing a statistical distribution is established for a set of historical occurrences of an event. Comparison is made between the baseline and at least one current occurrence of the same event. Any current occurrence that is anomalous vis-à-vis the baseline is considered a possible leading indicator. According to some inventive embodiments of graphical presentation of such comparison, at least one graphical baseline comparative display component is rendered that includes a “bar” (describing a historical statistical distribution with respect to a criterion pertaining to occurrence of an event) and a “slider” (describing one or more current occurrences of the event). The bar includes at least one band representing a statistical mean range, and at least one band representing a statistical outlier range. Situation of the slider along the bar indicates whether and to what extent the current occurrence(s) is/are anomalous vis-à-vis the baseline.

The invention relates to a complete method for identifying and screening heat-resistant bottle gourd stocks, which belongs to the field of biology. Rapid screening of heat-resistant materials for variety breeding is based on establishment of a reliable heat resistance identification method. The natural field identification method is susceptible to environment and unable to accurately screen target materials. Therefore, inventing a complete method for rapidly and accurately identifying bottle gourd stock heat resistance by artificial stressing and statistical means is urgent. According to the technical scheme, the complete method includes: using bottle gourd high-temperature seeds to sprout and testing electric conductivity in the seedling stage; calculating identification indexes, namely relative germination rate (40-45 DEG C/30-35 DEG C), relative germination index (40-45 DEG C/30-35 DEG C) and relative electric conductivity (6h/0h); and identifying and screening the bottle gourd seeds by the clustering function of software SPSS13.0. The complete method is simpler in operation flow, consumes less time, is lower in cost, and can be used for identifying heat resistance of the bottle gourd stock material more quickly, more accurately and more conveniently.

An automatic digital image characterization system has a feature extractor, including a segment processor and a feature processor. The segment processor is connected for receiving an image in the form of digitized pixel values; each pixel value having an amplitude and being associated with positional information in the form of column and row values. The feature processor converts the image information into column and row axis functions having calculated values of statistical mean amplitude and standard deviation. A system processor registers images, senses image changes, locates objects and detects hidden information.

According to typical inventive practice, a baseline describing a statistical distribution is established for a set of historical occurrences of an event. Comparison is made between the baseline and at least one current occurrence of the same event. Any current occurrence that is anomalous vis-à-vis the baseline is considered a possible leading indicator. According to some inventive embodiments of graphical presentation of such comparison, at least one graphical baseline comparative display component is rendered that includes a “bar” (describing a historical statistical distribution with respect to a criterion pertaining to occurrence of an event) and a “slider” (describing one or more current occurrences of the event). The bar includes at least one band representing a statistical mean range, and at least one band representing a statistical outlier range. Situation of the slider along the bar indicates whether and to what extent the current occurrence(s) is/are anomalous vis-à-vis the baseline.

The present invention relates to the technical field of piling, in particular to a digital construction system of a gravel pile machine, which includes a metering device for pile driving depth, a pile point positioning device, a statistical device for crushed stone input, a bearing layer current detection device, a data processing module and Data processing terminal. The digital construction system of the gravel pile driver of the present invention can ensure the continuity, accuracy and real-time performance of piling management, and is in line with the development direction of the country in information construction.