74 results about "Weight statistics" patented technology

In a hierarchical profile, each node represents at least one feature of behavioral data collected about an entity profiled, with the topmost node selected as the “statistically most informative” feature of the data. A profile can cover numerous domains and be predictively very powerful in each domain. A number of observations can be “aggregated” together into a single datapoint. In use, the structure of the profile is compared against current information associated with the entity to produce a recommendation or prediction. If the profile represents at least some data aggregation, then new observations are folded into the profile based on statistical weights of the aggregations. Because of the way the profile is created and updated, its hierarchical structure maps the collected observations. Therefore, as new observations are incorporated, if the new observations change the profile's structure significantly, then it can be hypothesized that something “interesting” has happened to the entity.

The present invention discloses a method for acquiring automatic exposure control parameters and a method for controlling automatic exposure control parameters and an imaging device. The core idea is to take the brightness weighted average value obtained according to brightness distribution weighted statistics of the image as the exposure control parameter. Then through adjusting the weighted coefficient of pixels in different brightness regions, control the influence of the pixel concentrated brightness regions on the brightness average value. Because the brightness distribution is the basis for determining weighted statistics, the control method of the present invention is not influenced by the scene assumption. Rather it can be universally adapted to a variety of different scenes, and the exposure control effect is not influenced by the position of scenes in the actual bright region/dark region and block distribution.

A novel and useful mechanism for the skinning of 3D meshes with reference to a skeleton utilizing statistical weight optimization techniques. The mechanism of the present invention comprises (1) an efficient high quality linear blend skinning (LBS) technique based on a set of skeleton deformations sampled from the manipulation space; (2) a joint placement algorithm to optimize the input skeleton; and (3) a set of tools for a user to interactively control the skinning process. Statistical skinning weight maps are computed using an as-rigid-as-possible (ARAP) optimization. The method operates with a coarsely placed initial skeleton and optimizes joint placements to improve the skeleton's alignment. Bones may also be parameterized incorporating twists, bends, stretches and spines. Several easy to use tools add additional constraints to resolve ambiguous situations when needed and interactive feedback is provided to aid users. Quality weight maps are generated for challenging deformations and various data types (e.g., triangle, tetrahedral meshes), including noisy, complex and topologically challenging examples (e.g., missing triangles, open boundaries, self-intersections, or wire edges).

A novel and useful mechanism for the skinning of 3D meshes with reference to a skeleton utilizing statistical weight optimization techniques. The mechanism of the present invention comprises (1) an efficient high quality linear blend skinning (LB S) technique based on a set of skeleton deformations sampled from the manipulation space; (2) a joint placement algorithm to optimize the input skeleton; and (3) a set of tools for a user to interactively control the skinning process. Statistical skinning weight maps are computed using an as-rigid-as-possible (ARAP) optimization. The method operates with a coarsely placed initial skeleton and optimizes joint placements to improve the skeleton's alignment. Bones may also be parameterized incorporating twists, bends, stretches and spines. Several easy to use tools add additional constraints to resolve ambiguous situations when needed and interactive feedback is provided to aid users. Quality weight maps are generated for challenging deformations and various data types (e.g., triangle, tetrahedral meshes), including noisy, complex and topologically challenging examples (e.g., missing triangles, open boundaries, self-intersections, or wire edges).

According to one aspect of the invention, a method of estimating geological location depths by converting horizon data from the time domain to the depth domain is provided, wherein the method comprises at least a data accumulation step and a data evaluation step, wherein the data evaluation step further comprises assignment of greater statistical weight to data derived from closer data acquisition points than to data derived from further data acquisition points using a weighted regression analysis, with distance being one of several weighting criteria. According to a further aspect of the invention, a method of estimating geological location depths is provided, wherein the method comprises a continuous, layer-by-layer computation of geological formation depths achieved by extracting values from horizon time data set at an exact geographic location of the next deeper horizon, thereby allowing interval computations to be carried out without the need for gridding. According to a still further aspect of the invention, a method of estimating geological formation depths is provided, wherein the method comprises estimating an expected error based on data scatter, and then allowing an alternative solution to be either partially or fully employed in areas where the accumulated data is insufficient to determine an acceptably reliable geophysical model.

The invention discloses a rapid and automatic exposure control method for the imaging of a complementary metal-oxide-semiconductor (CMOS) image sensor. The number of stepping regulation times is reduced. The method comprises the following steps of: dividing illumination brightness into five grades, establishing an exposure characteristic mathematical model, describing each grade of illumination brightness according to light intensity under the mathematical model, and establishing a corresponding light intensity exposure parameter comparison table; calculating a statistical brightness value of a current frame in a partition weight statistics way, reading current exposure parameters, and calculating light intensity under a current exposure characteristic mathematical model; and finishing presetting exposure parameters in the light intensity exposure parameter comparison table in a table lookup way.

There is provided a method and system for obtaining an enhanced estimate of bit error rate performance. A receiver module counts a predetermined number of bit errors and concurrently measures the time taken for the predetermined number of bit errors to occur. In this way an estimate of the bit error rate (BER) is obtained which has the same statistical weight regardless of the numerical value of the BER. The estimate of BER can subsequently be used to optimise the parameters of the system such that the true value of BER is at a minimum.

In a hierarchical profile, each node represents at least one feature of behavioral data collected about an entity profiled, with the topmost node selected as the “statistically most informative” feature of the data. A profile can cover numerous domains and be predictively very powerful in each domain. A number of observations can be “aggregated” together into a single datapoint. In use, the structure of the profile is compared against current information associated with the entity to produce a recommendation or prediction. If the profile represents at least some data aggregation, then new observations are folded into the profile based on statistical weights of the aggregations. Because of the way the profile is created and updated, its hierarchical structure maps the collected observations. Therefore, as new observations are incorporated, if the new observations change the profile's structure significantly, then it can be hypothesized that something “interesting” has happened to the entity.

The image generation method and system generates an image using a predetermined iterative reconstruction technique from cone beam data that has been expanded by adding additional data, and an instance of the iteration process is weighted according to a corresponding validation weight during the reconstruction. Optionally, an instance of the iteration process is weighted according to a combination of weights during the reconstruction. The predetermined combination of the weights includes axial weights based upon a validity value of the expanded data and statistical weights.

A system and method include acquisition of projection data from a scanned object, the set of projection data comprising a plurality of projection measurements. The system and method also include calculation of a set of modified statistical weights from the projection data, wherein a respective modified statistical weight of the set of modified statistical weights comprises a deviation from an inverse variance of a corresponding projection measurement of the projection data. The system and method further include reconstruction of an image of the scanned object using the set of modified statistical weights as coefficients in an iterative reconstruction algorithm.

The invention relates to a target detecting method of weighted robust broadband beam forming. The target detecting method comprises theoretical analysis, theoretical derivation, numerical simulation, algorithm improvement and result verification, and comprises the following steps: according to the characteristic that radiated noise of an underwater target contains a high-strength steady line spectrum, utilizing the characteristics that an amplitude difference between a main lobe and a minor lobe of frequency unit beam forming of the line spectrum of the target is larger and steadier, and an amplitude difference between a main lobe and a minor lobe of frequency unit beam forming of the noise is smaller and more random, firstly optimizing each frequency band beam forming by a second-order cone so as to obtain high gain beam forming of a low side lobe; then forming a weighting factor by utilizing a difference between the main lobe and the minor lobe of each frequency unit beam forming; then performing weighting statistics on each frequency unit beam forming by utilizing the weighting factor. The target detecting method can restrain the interference of background noise energy, enhance the gain of the signal to noise ratio of the target detection, overcome the difficulties of four-dimensional display of detecting a traditional line spectrum, improve the properties of an energy accumulation detecting method for long-range target detection, and improve the robustness of general broadband beam forming.

An embodiment of the invention provides a method and a device for performing histogram equalization processing on an image. The method mainly comprises steps as follows: calculating the distance between each pixel point in the image and a center pixel point; calculating a histogram statistical weight of each pixel point in the image according to the distance between each pixel point in the image and the center pixel point; performing weighted grey level histogram statistics of each grey level on the image respectively according to the histogram statistical weight of each pixel point in the image; performing histogram equalization processing on the image according to a weighted grey level histogram statistic result of each grey level of the image. According to the embodiment, different statistical weights are adopted for the pixel points according to spatial distribution positions of the pixel points in the image, so that a vision concerned area of people, namely, a center area of the image, can be stressed in the processed image, differentiated contrast enhancement processing is performed on different areas of the image, and the contrast ratio of the vision concerned area in the image is effectively enhanced.

A word vector representation method based on Chinese language element and pinyin joint statistics comprises the following steps of 1, collecting internet text information to construct a corpus, and conducting text cleaning and word segmentation processing on the constructed corpus; (2) carrying out word segmentation processing on the Chinese corpus, converting the processed Chinese corpus into pinyin information which does not reserve tone information, and then respectively carrying out statistical weights TFc, IDFc, TFp and IDFp on word frequency statistics and inverse document probability ofthe morphemes and pinyin characteristics in the training set corpus and the whole document; (3) constructing a Chinese single morpheme representation vector based on a Chinese word representation model of contextual morpheme and pinyin joint statistics; And (4) training a three-layer neural network on the basis of the step (3) for predicting the central target word. According to the method, the adaptability of an offline dictionary and the corpus data scale can be met, large-scale unlabeled internet information text data can be directly learned, the consideration of a conventional word embedding model on Chinese language difference characteristics can be improved, and the representation and recognition accuracy of wrongly written words can be improved.

It is provided a computer system, comprising a plurality of computers configured to execute processing in response to requests received from a plurality of external systems. The plurality of computers each share an acceptance weight statistic value calculated by each of the plurality of computers with another computer within the same network segment. The processor of each of the plurality of computers is configured to: receive a broadcast transmitted from one of the plurality of external systems to the same network segment; determine whether to respond to the received broadcast by referring to the shared acceptance weight statistic value; and send a response to the one of the plurality of external systems that has transmitted the broadcast in order to allow the one of the plurality of external systems to transmit a processing request in a case where it is determined to respond to the received broadcast.

It is provided a computer system, comprising a plurality of computers configured to execute processing in response to requests received from a plurality of external systems. The plurality of computers share an acceptance weight statistic value calculated by each of the plurality of computers with another computer within the same network segment. The processor of each of the plurality of computers is configured to: receive a broadcast transmitted from one of the plurality of external systems to the same network segment; determine whether to respond to the received broadcast by referring to the shared acceptance weight statistic value; and send a response to the one of the plurality of external systems that has transmitted the broadcast in order to allow the one of the plurality of external systems to transmit a processing request in a case where it is determined to respond to the received broadcast.

The invention proposes a method for implementing a consensus mechanism of a blockchain system. The method comprises the following steps: creating a system node weight table when the blockchain systemis initialized; when the current production node in the blockchain system is producing a block, querying the ip address of each node according to the system node weight table to determine whether there is a dropped node in the blockchain system; if there is a dropped node, decrementing the node weight value of the dropped node by 1, and updating the system node weight table; and when production nodes are generated based on the dpos consensus mechanism, selecting production nodes according to the number of votes of each node and the node weight value of each node. Therefore, the method providedby the invention links the offline time of the nodes with the statistical weight of the node voting number, so that even if the nodes that are frequently dropped have a high number of votes, the statistical weight of the voting number is not too high, thereby greatly reducing the possibility that the nodes that are often dropped become block production nodes, and ensuring that the blockchain system operates efficiently.

The invention discloses a network identity relationship reliability calculation method, comprising obtaining a plurality of second network identities associated with a plurality of first network identities to be queried, and utilizing the scene to which each of the second network identities belongs as a connection to form a network identity relation graph; and obtaining the scene statistical weight of adjacent network identity relations in the network identity relation graph to calculate the reliability of any pair of network identity relations in the network identity relation graph. Through building the network identity relation graph, the method can more rapidly calculate the reliability of a pair of network identity relations, and further be in favor of network data safety and maintenance.

Approaches are described for addressing artifacts associated with iterative reconstruction of image data acquired using a cone-beam CT system. Such approaches include, but are not limited to, the use of asymmetric regularization during iterative reconstruction, the modulation of regularization strength for certain voxels, the modification of statistical weights, and/or the generation and use of synthesized data.

The invention discloses a method for Raman spectrum characterization of heterogeneous foam layer minerals in antimony ore flotation. The method comprises the following steps: acquiring a spectrum of a pure antimony sulfide substance; collecting foam layer samples in multiple times from the same flotation cell at a flotation site; measuring the obtained samples by establishing a large-spot Raman spectrum detection system; preprocessing the samples by adopting preprocessing methods, such as smooth denoising, polynomial fitting baseline deduction and the like; identifying the number of spectral peaks of the preprocessed foam layer samples by using a peak searching algorithm; establishing a spectral peak information table; carrying out matching identification on the spectral peaks of the foam layer samples and the pure substance antimony sulfide by using a main characteristic peak matching algorithm; classifying all the foam layer samples by combining a K-means clustering method; carrying out weighted statistic on different categories of probabilities to obtain a Raman spectrum of the mineral content of a foam layer. According to the method disclosed by the invention, the spectral peaks of the foam layer samples are identified by establishing the large-spot Raman spectrum detection system, so that the characterization of the foam layer sample spectrum of the flotation cell is realized, the non-uniformity in the spectrum detection of the heterogeneous foam layer can be effectively overcome, the spectrum of the heterogeneous foam layer can be rapidly and completely characterized, and a basis is laid for rapid and real-time detection of the mineral content of the foam layer.

The invention discloses a statistical processing method and system of usual achievements in a SPOC (Small Private Online Course) platform. The statistical processing method is characterized by comprising the following steps: S1: a student terminal or a teacher terminal sends task completion data to a server, and the server receives and processes the task completion data to obtain the achievement data of a target student terminal; S2: the teacher terminal sends a usual achievement weighting statistics method instruction to the server, and the server carries out weighting calculation according to the instruction to obtain the weighting usual achievements of each student terminal; and S3: the teacher terminal or the student terminal sends a query signal to the server, the server calls the related achievement data according to the received query signal, sends the achievement data to the teacher terminal or the student terminal, and can realize the statistical processing on multi-source achievement data in the SPOC platform from multiple dimensionalities to form the construction of an achievement database which is updated in real time. In addition, an achievement data processing stat between two query requests is reasonably designed to greatly improve platform query efficiency, reduce a server handling capacity and prevent the server from operating under high load for a long time.

The invention provides a Diff scoring method. The method comprises the following steps of acquiring a first webpage and a second webpage which are to be compared; extracting element information in the first webpage and element information in the second webpage andcomparing the corresponding element information in the first webpage and the second webpage to obtain a Diff result; endowing the element information with different weights, and analyzing the Diff result according to weight statistics to acquire similarity values of the first webpage and the second webpage. The invention further provides a system using the method. An efficient and automatic webpage effects test can be realized by the Diff scoring method.

This invention relates to a network abnormal test method based on weight statistic model of the time segment including observing the actions of a master unit by an abnormal observer to generate an attribute for describing these actions, each one stores the registration of a behavior of the master unit and timely merges the attributes of the current and the stored then to judge the abnormal behaviors by comparing them and the time segment weight.

The invention relates to a hull structure weight statistics method based on a three-dimensional model. The method comprises the steps of performing Boolean operation merging on all structure design part models to obtain a whole ship model; and then setting a longitudinal cutting interval according to calculation requirements, cutting the whole ship model into sections in a longitudinal direction,sequentially outputting structure weight load distribution values of the sections and performing statistics on structure weight distribution of a whole ship. According to the method, full computer operation can be realized, so that the statistical speed is increased; a weight load cutting interval can be set according to needs (according to original position-based partition or smaller partition units), so that the calculation precision is greatly improved; and in addition, the operation is carried out by utilizing an existing CATIA physical model, so that the workload of re-modeling is omitted. By use of the method, a designer can be freed from a lot of tedious design and modeling work, the working efficiency is improved, and more efficient data support is provided for fine calculation ofthe total vibration of the ship.

In a hierarchical profile, each node represents at least one feature of behavioral data collected about an entity profiled, with the topmost node selected as the “statistically most informative” feature of the data. A profile can cover numerous domains and be predictively very powerful in each domain. A number of observations can be “aggregated” together into a single datapoint. In use, the structure of the profile is compared against current information associated with the entity to produce a recommendation or prediction. If the profile represents at least some data aggregation, then new observations are folded into the profile based on statistical weights of the aggregations. Because of the way the profile is created and updated, its hierarchical structure maps the collected observations. Therefore, as new observations are incorporated, if the new observations change the profile's structure significantly, then it can be hypothesized that something “interesting” has happened to the entity.