129 results about "Weighted distance" patented technology

The disclosed System enables word-level text entry on a small displayed keyboard by tracing an input path that begins on or near the key of the first letter, passes through or near the key of each letter in sequence, and terminates in the vicinity of the key of the last letter. The input path is processed by scoring it against words in a database that includes an indication of relative frequency. A correctly spelled word is output even when the input path corresponds to an incorrect spelling of a word. Words are ranked according to a score calculated from the weighted distances from each associated key to determined input path points, further weighted by the frequency of use and by other characteristics of the input path. Alternate word choices are presented to the user in a manner to minimize distraction. Efficient editing mechanisms and other enhancements are included.

The disclosed System enables a small virtual keyboard on a touch-screen to be used to enter a word by contacting the keyboard on or near the key of the first letter, tracing through or near the key of each letter in sequence, and lifting the stylus from the keyboard in the vicinity of the key of the last letter. The input pattern is matched by scoring it against words in a database which includes an indication of relative frequency. A correctly spelled word is matched even when the input pattern corresponds to an incorrect spelling of a word. Words are ranked according to a score calculated from the weighted distances from each associated key to determined input path points, further weighted by the frequency of use and by other characteristics of the input path. Alternate word choices are presented to the user in a manner to minimize distraction.

The disclosed System enables word-level text entry on a small displayed keyboard by tracing an input path that begins on or near the key of the first letter, passes through or near the key of each letter in sequence, and terminates in the vicinity of the key of the last letter. The input path is processed by scoring it against words in a database that includes an indication of relative frequency. A correctly spelled word is output even when the input path corresponds to an incorrect spelling of a word. Words are ranked according to a score calculated from the weighted distances from each associated key to determined input path points, further weighted by the frequency of use and by other characteristics of the input path. Alternate word choices are presented to the user in a manner to minimize distraction. Efficient editing mechanisms and other enhancements are included.

A method of operation of an advertisement delivery system includes: receiving a selection for a category of interest; generating search results for the selection, the search results based on a current location for locating a device providing the selection; generating a weighted distance based on distances of the search results from the current location; generating a weighted relevancy based on relative matches of the search results and the selection; generating a weighted customization with the search results sharing a common attribute that is predefined; and delivering a notification from the search results by an aggregation of the weighted distance, the weighted relevancy, and the weighted customization, the aggregation meeting or exceeding a threshold for displaying on the device.

A system and method for facilitating target acquisition is presented. Upon detecting a triggering event to display expanded targets, i.e., icons representing applications, services, folders, and the like, the computer system generates expanded targets and displays them for target acquisition. The expanded targets typically include their source target, and are expanded such that a user may more easily acquire that source target. According to one embodiment, the expanded targets are generated as Voronoi polygons. Alternatively, the expanded targets may be generated as polygons based on a weighted distance based on the area previously assigned to the expanded target.

A method is provided for data classification that achieves improved interpretability and accuracy while preserving the efficiency and scalability of univariate decision trees. To build a compact decision tree, the method searches for clusters in subspaces to enable multivariate splitting based on weighted distances to such a cluster. To classify an instance more accurately, the method performs a nearest neighbor (NN) search among the potential nearest leaf nodes of the instance. The similarity measure used in the NN search is based on Euclidean distances defined in different subspaces for different leaf nodes. Since instances are scored by their similarity to a certain class, this approach provides an effective means for target selection that is not supported well by conventional decision trees.

A network weight distance vector positioning method of radio transducer includes carrying out weight treatment on average each jump distance of each received anchor node based on DV-hop positioning means and considering estimated average each jump distance of multiple anchor nodes, calculating distance between unknown node and anchor node by utilizing final average each jump distance for effectively decreasing estimation deviation and for effectively raising the positioning accuracy of complete network.

An object pose estimating and matching system is disclosed for estimating and matching the pose of an object highly accurately by establishing suitable weighting coefficients, against images of an object that has been captured under different conditions of pose, illumination. Pose candidate determining unit determines pose candidates for an object. Comparative image generating unit generates comparative images close to an input image depending on the pose candidates, based on the reference three-dimensional object models. Weighting coefficient converting unit determines a coordinate correspondence between the standard three-dimensional weighting coefficients and the reference three-dimensional object models, using the standard three-dimensional basic points and the reference three-dimensional basic points, and converts the standard three-dimensional weighting coefficients into two-dimensional weighting coefficients depending on the pose candidates. Weighted matching and pose selecting unit calculates weighted distance values or similarity degrees between said input image and the comparative images, using the two-dimensional weighting coefficients, and selects one of the comparative images whose distance value up to the object is the smallest or whose similarity degree with respect to the object is the greatest, thereby to estimate and match the pose of the object.

Propagating information in a computer network, in one aspect, may include detecting an online action performed by a user on a content presented on a computer. The content may be annotated with an identifier. A semantic graph may be searched for a semantic node representing the identifier. The semantic graph may be searched for one or more other semantic nodes representing one or more other identifiers that meet a semantic similarity threshold based on weighted distances between the semantic node and the one or more other semantic nodes. One or more other users represented in a social graph may be determined that have interest in one or more topics represented by the identifier and the one or more other identifiers. The online action on the content may be propagated to the one or more other users.

The embodiment of the invention discloses a method and a device for locating a wireless sensor terminal. The method comprises the following steps: on the basis of a wireless signal energy attenuation principle, mapping received signal strength indication (RSSI) obtained by all nodes onto probability weighted distance D in an off-line training manner by virtue of a Bayesian model; and more accurately locating the nodes according to a maximum likelihood estimation method and a Kalman filtering method from static and dynamic aspects. In the method, RSSI modeling is carried out statistically, which overcomes the defects such as influence on wireless terminal location caused by antenna directivity, environment and other factors for a small and medium sized mobile terminal signal as well as higher cost caused by the addition of a special sensor in the prior art; and in addition, relative to a classic single linear model or a segmented linear model, the model is updated by an on-line learning method so as to more accurately describe the situation of larger variance in a sample acquired by a small-sized wireless terminal, thus improving the practicability and applicability.

The invention discloses a method for locating mobile users of a single base station on the basis of multi-parameter estimation. The method includes distinguishing diameter arriving signals by the aid of time of arrival (TOA), and measuring angles of arrival of diameter signals by the aid of technologies for estimating the angles of arrivals (AOA) so as to acquire the orientation of the mobile users relative to the base station; measuring the distances from the single base station to the mobile users by the aid of the TOA and channel state information (CSI) and carrying out weighting processing on distances measured by the aid of the TOA and distances measured by the aid of the CSI so as to obtain weighted distances; combining the measured angles of arrival and the measured weighted distances with one another and acquiring the locations of the mobile users by means of estimation. The method has the advantages that only the single base station is required, three types of measurement parameters which are the TOA, the AOA and the CSI are combined with one another, accordingly, the quantities of base stations and influence of multipath effects can be reduced, the cost can be lowered, and the locating precision can be improved.

The invention belongs to the technical field of power quality analysis and especially relates to a node voltage sag severity comprehensive assessment method based on a weighted ideal point method. The method is characterized in that the method comprises the following steps: to begin with, establishing an attribute set and a scheme set; then, determining combination weight of each index in the attribute set based on an entropy weight method and a variation coefficient method; and finally, carrying out voltage sag severity comprehensive assessment based on the weighted ideal point method. Weighted distance between each scheme and positive and negative ideal solutions in the ideal point method and relative closeness between the scheme and the positive ideal solution are calculated respectively, and the schemes are ranked in a descending order in sequence to obtain an optimal scheme order. The method reflects voltage sag severity from the perspectives of frequency, duration and amplitude angle, and reflects influencing characteristics of sag frequency on the voltage sag severity from perspectives of the part and the whole, so that erroneous judgment due to single-index assessment is effectively prevented, voltage sag information of each node can be reflected more comprehensively and accurately, and the obtained result is objective, accurate and more realistic.

An embodiment of the application provides a human face identification method, device and system. Based on coordinates of human face characteristic points, a human face skin confidence area is determined, and an average RGB color value of the human face skin confidence area is used as a reference skin pixel value. Because the average RGB color value is obtained based on an image to be identified, a phenomenon that an identification result error is caused due to human face skin color difference in the image to be identified or human face skin color difference caused by light ray difference can be prevented. Weighted distance between all pixel points in a middle image which is converted into a preset color space and a middle average color of the preset color space corresponding to the average RGB color value of the human face skin confidence area is calculated, and whether all the pixel points belong to a skin area can be determined based on a determining criterion that a probability that the pixel points do not belong to the skin area is proportionate to the weighted distance. The human face identification method provided in the embodiment of the application is high in robustness.

Provided is a process of and apparatus for spatially indexing geographic items. The process may include obtaining geographic-item data identifying geographic items, the geographic location of each item, and an attribute of each item, wherein the geographic-item data identifies values of key-value pairs to be formed in a spatial index; obtaining a plurality of geographic-location keys each corresponding to a geographic area, the geographic-location keys identifying keys of the key-value pairs to be formed in the spatial index; and pairing each geographic-location key with an item among the geographic-item data. Pairing may be performed by: calculating distances between the geographic location of each of the items and the geographic-location key; weighting each of the distances based on the attribute of the item corresponding to that distance; and selecting the geographic item having the closest attribute-weighted distance as the item to be paired with the geographic-location key.

The invention provides an electric power material distribution center location selection method. The method comprises the following steps that A, a destination region is divided into sub-regions; B, distribution centers are arranged at different logistics nodes in each sub-region, and the sum of weighted distances from suppliers and the distribution centers at different positions in the sub-regions to a demand point is determined; C, the position of the distribution center corresponding to the minimum weighted distance in each sub-region is determined as the position of the distribution center of the sub-region. By the adoption of the electric power material distribution center location selection method, the characteristics of a supplier inventory management pattern and a joint inventory management pattern can be considered, and a proper location of an electric power material distribution center is determined based on the virtual inventory technology and the time satisfaction degree; therefore, complex electric power distribution system requirements are met, resources are optimized, and the service quality is improved.

It is shown a method to move focus from a first user interface element to a second user interface element shown on a display of a mobile communication terminal, said mobile communication terminal further comprising an input device. The method comprises the steps of: detecting a directional input via said input device, said input indicating a desired direction to move; determining a set of candidate user interface elements being eligible to receive focus; for each candidate user interface element in said set of candidate user interface elements, determining a weighted distance between said candidate user interface element and said first user interface element by applying a function including, as an input parameter, an overlap between said first user interface element and said candidate user interface element in a direction orthogonal to said desired direction; and determining said second user interface element to be a particular candidate user interface element in said set of candidate user interface elements that has a minimum weighted distance to said first user interface element.

An object pose estimating and matching system is disclosed for estimating and matching the pose of an object highly accurately by establishing suitable weighting coefficients, against images of an object that has been captured under different conditions of pose, illumination. Pose candidate determining unit determines pose candidates for an object. Comparative image generating unit generates comparative images close to an input image depending on the pose candidates, based on the reference three-dimensional object models. Weighting coefficient converting unit determines a coordinate correspondence between the standard three-dimensional weighting coefficients and the reference three-dimensional object models, using the standard three-dimensional basic points and the reference three-dimensional basic points, and converts the standard three-dimensional weighting coefficients into two-dimensional weighting coefficients depending on the pose candidates. Weighted matching and pose selecting unit calculates weighted distance values or similarity degrees between said input image and the comparative images, using the two-dimensional weighting coefficients, and selects one of the comparative images whose distance value up to the object is the smallest or whose similarity degree with respect to the object is the greatest, thereby to estimate and match the pose of the object.

The invention discloses a frequency change signal two-dimensional direction finding method and device adopting two sensors. The method comprises the following steps of acquiring the collected phase differences phi n, the frequencies fn and the signal-to-noise ratios SNRn of the two sensors; randomly dividing the data of the collected phase differences into K groups; for each group of the collectedphase differences, calculating weighted distances between complex numbers composed of the collected phase differences and complex numbers composed of phase differences corresponding to angles on an incident angle grid, thereby generating two-dimensional distance matrixes; searching for each distance matrix to obtain a matrix serial number corresponding to a minimum value in each distance matrix;defuzzifying the collected phase differences to obtain a non-fuzzy phase difference matrix; solving the two-dimensional incident angles; sequentially sorting K groups of the two-dimensional incident angles, and comparing a current result with a previous result; and if K comparison values L<1>-L<K> are all smaller than a threshold, outputting the current result, otherwise, according to the currentresult, generating K groups of theoretical phase differences, calculating the distances, defined in the description, between the collected phase differences phi n and the theoretical phase differencesdefined in the description, comparing the distances defined in the description, and re-classifying the phi n to the corresponding k-th group when the distance defined in the description is minimum.

The invention discloses a circular ring model routing method based on a fuzzy C-means clustering algorithm. The problem of link stability in a mobile ad hoc network is mainly solved. The invention provides a circular ring model fuzzy C-means clustering algorithm (FCMCRR) divided by radius. In the clustering stage, a Vikor multi-standard decision is used for selecting the optimal initial clusteringcenter, and the situation that the algorithm is trapped in local optimum is avoided. In the clustering stage, a fuzzy C-means clustering algorithm is used, and the optimal classification is searchedaccording to an objective function method. An objective function considered by the invention represents a weighted distance quadratic sum from various data nodes to a corresponding clustering center,and groups of the nodes are distinguished through distances, so that a fuzzy division matrix and the clustering center of the nodes are calculated and modified. The routing strategy based on the circular ring model provided by the invention can ensure that the relay node can effectively enhance the routing performance and enhance the link stability.

A system and method for adaptive cruise control for low speed following are disclosed. A particular embodiment includes: receiving input object data from a subsystem of an autonomous vehicle, the input object data including distance data and velocity data relative to a lead vehicle; generating a weighted distance differential corresponding to a weighted difference between an actual distance between the autonomous vehicle and the lead vehicle and a desired distance between the autonomous vehicle and the lead vehicle; generating a weighted velocity differential corresponding to a weighted difference between a velocity of the autonomous vehicle and a velocity of the lead vehicle; combining the weighted distance differential and the weighted velocity differential with the velocity of the lead vehicle to produce a velocity command for the autonomous vehicle; adjusting the velocity command using a dynamic gain; and controlling the autonomous vehicle to conform to the adjusted velocity command.

Embodiments of the present application disclose a method and apparatus for aligning three-dimensional point clouds, which relate to the technical field of data processing and contribute to improving the accuracy of relative pose determination in a point cloud alignment process. The method comprises the following steps of: acquiring at least two point pairs, wherein the point pairs are composed ofa first point in a target point cloud and a second point corresponding to the first point in a source point cloud; According to the weighted distance from the surface of at least two point pairs, determining the relative pose between the target point cloud and the source point cloud, A weighted distance from the surface is obtained by accumulating the product of the distance from the surface of each of the at least two point pairs and the weight corresponding to each point pair, a projection length of a distance between a first point and a second point on a target normal of a tangent plane having a second point as a tangent point, the target normal and the tangent plane intersecting the second point, the weights being used to characterize the correlation of a corresponding point of the first point in a depth image of the target point cloud with a point within a preset range of the periphery of the corresponding point; Adjust the posture of the target point cloud according to the relative posture.

The invention relates to a floor identification method based on building open edge distance weighting. An extra sensor device or a complex algorithm is needed by current methods, and requirements on the operational capability and storage capability of a device are high. The floor identification method based on building open edge distance weighting comprises the steps of: deploying firstly, and then locating floors. The deployment comprises the sub-steps of: firstly, determining a minimum distance between each AP and an open edge of a floor where each AP is, so as to obtain an average value of the minimum distances; then calculating a floor positioning weight for each AP to obtain each measuring point, and measuring to obtain signal intensity vectors. The floor location comprises the sub-steps of: firstly, measuring a signal intensity vector of the current position; then calculating a signal intensity vector weighted distance between each measuring point and the current position; regarding the floor where the measuring point with the minimum signal intensity vector weighted distance as the floor where the current currently is. As the signal intensity vector distance is calculated based on the distance between each AP and the open edge of the floor as a weight factor, and a traditional algorithm is amended, a more precise floor locating result is obtained.

A system and method for utilizing a graphic equalizer in performing image search procedures includes a histogram calculator for creating sets of histograms that represent corresponding images. A graphic equalizer is configured to select weighting parameters for performing the image search procedure. A feature detector calculates distance measures between histogram comparison pairs of a query image and subject images. The feature detector applies the weighting parameters to the distance measures to produce weighted distance measures. The feature detector next combines the weighted distance measures from the histogram comparison pairs to produce a composite distance measure for each of the subject images. The feature detector may then identify one or more of the subject images that are similar to the query image by analyzing the composite distance measures.

The invention provides a weighted DV _ Hop node positioning method based on a minimum mean square error criterion, and the method comprises the steps: setting other anchor nodes to have the same weight under the minimum mean square error criterion, and obtaining a preliminary estimation value of the average distance of each hop of the anchor nodes; setting weights for other anchor nodes for the second time, and obtaining the corrected average hop-by-hop distance of the anchor nodes under the minimum mean square error criterion; calculating the connectivity of each adjacent anchor node and theaverage distance error of each hop; calculating the average hop distance of the unknown node and the estimated distance from the unknown node to the anchor node according to the average hop distance of the adjacent anchor nodes and the normalized weight value; and setting a linear solution of a weighted least square method as an iterative initial value, minimizing a weighted distance estimation error objective function through a nonlinear weighted iterative method, and taking an iterative result as a positioning coordinate of an unknown node. According to the method, the more accurate averagehop distance between the anchor node and the unknown node can be obtained, the calculated amount is small, and the positioning accuracy and stability are improved.

A method and apparatus for managing controls on the screen of a computer controlled display. The preferred embodiment of the present invention provides for quick and efficient activation and deactivation of controls by designating a number of controls as a control grouping. The preferred embodiment then collectively activates or deactivates the designated number of controls using an identifier for the control grouping. Additionally, after a user terminates cursor movement, the preferred embodiment automatically positions a cursor on an ideal control. The preferred embodiment determines the ideal control (1) by removing from consideration any controls which are (a) not visible to the user, or (b) located at non-optimal positions on the screen, and (2) by calculating a weighted distance for each remaining control. The preferred embodiment calculates the weighted distances by comparing the previous cursor movements made by a user with application specified parameters. After calculating a weighted distance for each remaining control, the preferred embodiment automatically positions the cursor on the control having a smallest associated weighted distance.

The invention discloses a fuzzy supervised classification method for a multiband remote sensing image based on non-equal weight distances. In the method disclosed by the invention, the non-equal weight distances of the cluster center of the remote sensing image and various land utilization types in different wavebands are redefined by adopting the manually extractive spectrum information of a training region based on a traditional FCM (File Compare Mask) classification method; and the degree of each pixel belonging to the different land utilization types is judged by utilizing the non-equal weight distances as an evaluation criterion, thereby realizing the fuzzy supervised classification of the remote sensing image. The method disclosed by the invention determines the cluster center and the distance value through the spectrum characteristics of the training region and obviously improves the classification efficiency and the classification accuracy.

The invention discloses a hydrological data abnormal mode detection method based on similarity measurement. The method is based on a linear piecewise representation KPRA-PLR algorithm of a key point,hydrological data is cut according to the definition of the key point, straight line fitting is carried out on each sub-sequence through the PLR algorithm, and the slope ai and the time interval deltat of a straight line are used for representing the sub-sequence; wherein each segmented sub-sequence is called as a meta-mode, adjacent meta-modes are combined to obtain a sequence mode, a weighted distance and an SDTW algorithm are respectively used for similarity measurement of the meta-mode and the sequence mode, and then an abnormal score of each sequence mode, namely a reciprocal of an average distance between the mode and other modes, is calculated; wherein the abnormal score is the k-nearest neighbor distance of the sequence mode Sx, and calculating a local abnormal factor LOF according to a k-nearest neighbor local detection principle. The abnormal mode detected by using the similarity measurement method is more accurate, and a new technology is provided for hydrological data abnormal mode detection from the perspective of data analysis.

The invention relates to an acoustic model combination method and device, and a voice identification method and system. The acoustic model combination method that is used for combining a plurality of acoustic models including a first acoustic model and a second acoustic model comprises the following steps: a distribution information obtaining step; to be specific, obtaining distribution information, being capable of reflecting an importance degree of a modeling unit in a to-be-identified language, of modeling units of at least first acoustic model and the second acoustic model or a model unit of at least the first acoustic model or the second acoustic model; a distance calculation step; to be specific, respectively calculating distances of this type of model forming element pairs formed by model forming elements with the same type of the first acoustic model and the second acoustic model; a weighting step; to be specific, carrying out weighting processing on the distances of this type of corresponding model forming element pairs by using the distribution information; a sorting step; to be specific, sorting of this type of model forming element pairs based on the weighted distances; and a combination step; to be specific, according to the sorting result, combining the first acoustic model and the second acoustic model so as to obtain a combined acoustic model.

The invention discloses an inter-frame scene matching method and a device based on multi-rotor unmanned aerial vehicle aerial video. The sparse optical flow method is used to extract the characteristic corner pairs from the target region image. According to the first geometrical space distance of each characteristic corner pair, the well area division of the target area image and the combination of characteristic corner pairs, the combination of characteristic corner pairs of the target is selected. Calculating a second geometrical space distance between two corner pairs of the transformed target characteristic corner pairs according to a perspective transformation matrix, and further calculating a sum of weighted distances of all target characteristic corner pairs in each target characteristic corner pair combination; the combined result of the target feature corner pairs with the smallest sum of weighted distances is taken as the final matching result. The invention can effectively cope with the complex and changeable motion shooting state of the multi-rotor unmanned aerial vehicle imaging device, and does not need to rely on flight data or attitude parameters of the multi-rotorunmanned aerial vehicle and the imaging device thereof.