280results about How to "Reliable extraction" patented technology

A passive keyless entry device includes a fixed unit and a portable unit. A signal receiving section of the portable unit includes three antennas for receiving a signal which is wirelessly transmitted from the fixed unit with respect to three directions which are at right angles to one another; three amplifiers; three detectors; a selector circuit for selecting one detection output by which a wake-up signal can be detected and in which the received signal valve of the antenna is comparatively high from among the detection outputs which are output from the detectors; a level comparator; first and second switches; and a counter.

To provide a human state estimating device which accurately estimates a human state. The human state estimating device includes: a storage unit (16) which stores reference data (17) in which a human state and a reference profile including a horizontal component of a standard microsaccade in the human state are corresponded to each other, for each of plural personal attribute information; a video obtaining unit (11) which obtains video of a user's eyeball, with an eyeball rotation angle accuracy of 0.05 degrees or higher, and a measuring speed of 120 samples per second or higher; an analyzing unit (12) which generates an actual-measurement profile including the horizontal component of the microsaccade, from fixational eye movement shown in the video; a personal attribute information obtaining unit (13) which obtains the user's personal attribute information; and an analyzing unit which estimates the human state by searching, in the reference data (17), for a reference profile that corresponds to the obtained personal attribute information and is closest to the actual-measurement profile.

A communication setup program eliminates the need for setting communication data common to multiple applications individually for each application. The communication setup program configures communication data that is reflected by the applications when each application is loaded, and provides a device selection module for selecting a target communication device from among one or more devices setup on the computer; a related application extraction module for extracting related applications that support the selected device from among a plurality of applications installed on the computer; a communication data setup module for configuring the communication data used by related applications to communicate with the selected device; and a communication data ID output module for providing a communication data ID for referencing the configured communication data to the extracted applications.

The invention provides a wave energy and ocean current energy integrated generator comprising an undersea guide caisson, a water turbine, a vibrating floater, a round void compartment, a fixing rack, a hydraulic integrated generating module, and three hydraulic cylinders. The water turbine is disposed in the undersea guide caisson. The vibrating floater disposed outside a transmission shaft of the water turbine floats on the water surface. The round void compartment is mounted on the transmission shaft and arranged above the vibrating floater. The fixing rack is arranged on the outer surface of the round void compartment. The hydraulic integrated generating module is disposed in the fixing rack. The hydraulic cylinders are disposed between the vibrating floater and the fixing rack and convert ocean current energy and wave energy from sea water into electric energy through the water turbine and the vibrating floater, respectively. The wave energy and ocean current energy integrated generator is capable of extracting wave energy and ocean current energy at the same time, the generating process is continual and controllable, the generator is high in operational reliability, output electricity quality is high, and economic efficiency is good; in addition, the invention further provides a power generation method using the wave energy and ocean current energy integrated generator.

The liquid ejection apparatus includes: a liquid ejection head including a nozzle which ejects liquid, a pressure chamber which is connected to the nozzle and is to be filled with the liquid, a pressure generating element which pressurizes the liquid in the pressure chamber, and a pressure determination element which determines a pressure inside the pressure chamber and outputs a pressure determination signal; a storage device which stores a peak value of the pressure determination signal output by the pressure determination element in a state where the nozzle ejects the liquid normally; a first ejection abnormality factor extraction device which extracts a first ejection abnormality factor by comparing the peak value stored previously in the storage device with the pressure determination signal output by the pressure determination element during a prescribed period for ejection abnormality determination; a threshold value variably setting device which sets a threshold value for extracting a second ejection abnormality factor according to a differential between the peak value stored previously in the storage device and a peak value of the pressure determination signal output by the pressure determination element during the prescribed period for ejection abnormality determination; a pulse generation device which is capable of generating pulses according to a comparison result between the threshold value set by the threshold value variably setting device and the pressure determination signal output by the pressure determination element during the prescribed period for ejection abnormality determination; and a measurement device which extracts the second ejection abnormality factor by measuring a time interval of the pulses generated by the pulse generation device.

The invention discloses a data warehouse based on data fusion and data mining and an application method of the data warehouse. The data warehouse mainly solves the problems that in the prior art, a data warehouse cannot meet requirements of users for reliability, consistency and sharing performance of storage and extraction of large amounts of data information. The data warehouse comprises a data extraction layer, a data storage layer and a data access layer, wherein the data extraction layer is used for extracting data in online transaction processing system, an external data source and off-line data storage media and leading the extracted data into the data storage layer; the data storage layer comprises an ODS used for storing the data which are subject-oriented, integrated and current or close to the current and constantly change, an EDW storing enterprise-level data and a data mart; the data access layer is used for accessing data in the data storage layer in a statement, image or data analysis mode and carrying out analysis prediction. According to the data warehouse based on data fusion and data mining and the application method, the aim of storing and accessing data safely, reliably and conveniently is achieved, and the data warehouse has high practical value and popularization value.

The invention relates to an establishing method of a regional CORS coordinate time series noise model. The establishing method is characterized by comprising the following steps that: step 1, observation data of a regional CORS station are obtained; step 2, GNSS data pre-processing software TEQC is adopted; step 3, GAMIT / GLOBK baselines are adopted to solve adjustment; step 4, a high-precision coordinate time series is established; step 5, singular spectrum analysis-based spatial filtering is performed; step 6, MLE estimation-based noise model selection is performed; and step 7, regional CORS velocity filed estimation is performed in view of colored noise models. According to the establishing method of the invention, time-domain frequency domain characteristic analysis is adopted to perform spatial filtering on the regional CORS time series; and maximum likelihood values are selected for different noise models of the regional CORS time series, so that judgment can be performed, and therefore, optimal noise models in the N (North), E (East) and U (altitude) are determined, and the regional CORS velocity filed can be estimated in view of the optimal noise models.

An image processing apparatus that receives an image from a scanner capable of optical scaling is provided by the present invention. It has an image scaling unit for performing digital scaling of a received image, and an information detecting unit for detecting encoded information from the received image. Unless the scaling factor is that suitable for optical scaling, the received image undergoes the digital scaling instead of the optical scaling. Before the received image undergoes the digital scaling, the information detecting unit detects the encoded information from the received image. The scaling using the image reading device capable of optical scaling enables more accurate analysis of the encoded information embedded in a source document.

The invention discloses a method and system for automatically extracting a building outline of a static three-dimensional map, and relates to the field of geographic information technology. The methodincludes the steps of loading a three-dimensional model in blocks according to the frame buffer size and the map resolution; obtaining a color buffer of a single building object by using a depth buffer partitioning algorithm; performing edge detection by using a Canny operator; then performing edge processing and connecting straight line segments; and next, based on the graph theory, taking a line segment as a vertex and the connection probability of the line segment as the weight of an arc, grouping the line segments by a perceptual organization method, and extracting the outline of a building model. The method and system in the invention can automatically and reliably extract the building outline in the static three-dimensional map from any angle of view.

The invention discloses an interest aware service recommendation method based on a MapReduce model. The method comprises the following steps of 1, acquiring a data set through the comment of a history user; 2, extracting the interests of an object user and the history user according to the corresponding keyword list and field word bank provided by the method, wherein the object user refers to the current user required to be recommended; 3, for each candidate Web service, calculating the similarity between the object user and the history user of the candidate Web service for searching users similar to the object user; 4, after calculating the similarity between the object user and the history user, predicting an individual score of the candidate Web service for the object user and providing an individual service ranking list according to a weighted average method, and recommending for the user according to the individual ranking list; 5, realizing the steps 2 to 4 through a Map-Reduce programming framework through four stages for parallel arrangement.

Even if the ratio between blue and green components of illumination light is changed, a plurality of types of blood vessels at different depths are reliably distinguished. A blue signal B, a green signal G, a red signal R is obtained by imaging the subject using a color CCD 44. A B / G image having a B / G ratio is generated. A superficial blood vessel extraction image is obtained by extracting a pixel, in which the B / G ratio is equal to or less than a boundary value Ls between the mucous membrane and the superficial blood vessel, from the B / G image. A medium-deep blood vessel extraction image is obtained by extracting a pixel, in which the B / G ratio is equal to or greater than a boundary value Ld between the mucous membrane and the medium-deep blood vessel. The boundary values Ls and Ld differ depending on the light amount ratio.

The invention discloses a driver abnormal posture monitoring method based on reinforcement learning. The method comprises the steps that after a driver driving video is acquired, driver face key points and skeleton key points which are far smaller than image pixel points in number are extracted through an OpenPose system, meanwhile, the face key points are subjected to spline interpolation for three times to construct face characteristics, and driver identity recognition is carried out. According to the key frame extraction method, based on a reinforcement learning mode, a corresponding rewardis obtained through an attitude detection model, and an action value function is updated according to each action of the reward and an attitude until a stable key frame extraction strategy suitable for each driver is obtained. Based on the driver dynamic behavior with time and space changes, a machine learning algorithm is used for training to obtain a posture detection model. And a safety earlywarning mechanism with a guiding property is established in combination with a protection motive theory. According to the invention, the real-time performance and accuracy of detection are improved, and the reliability of safety early warning is enhanced.

A method and system for reliably estimating inspiration-to-expiration ratio from an acoustic physiological signal. A background sound level is set to an energy level whereat a predetermined share of data points on an energy envelope is below the energy level, after which respiration phase start and end times are determined at energy crossings above the background sound level, enabling more reliable determination of respiration phases. Moreover, reliably determined respiration phase start and end times, in addition to being used to estimate inspiration-to-expiration ratio, are applied to other purposes, such as estimating respiration period, validating an independently computed respiration period and / or adjusting a sampling window of the acoustic physiological signal, reducing system complexity and conserving computational resources.

The invention discloses a power distribution network single-phase ground fault section locating method and a power distribution network single-phase ground fault section locating system, which realizesection locating for a power distribution network single-phase ground fault. The method comprises the following steps: acquiring current waveform data of a plurality of fault samples in a power distribution network at several nodes, and extracting waveform characteristic quantity of each fault sample at the several nodes; based on the waveform characteristic quantity of each fault sample at the several nodes, constructing a topological matrix of each fault sample; calculating a random matrix characteristic value of each fault sample, and constructing a characteristic value set of each fault sample; clustering all the sample characteristic value sets, and obtaining a clustering center point of each fault section; calculating a random matrix characteristic value of a to-be-located fault sample, searching for the clustering center point from which distance to the random matrix characteristic value of the to-be-located fault sample is lowest, and determining the fault section.

The invention relates to an offshore doubly fed motor stator winding turn-to-turn short circuit early fault identification method, and is used for judging the doubly fed motor stator winding turn-to-turn short circuit and determining the phase of the turn-to-turn short circuit. The method comprises the following steps that 1) the three-phase signals of an offshore doubly fed motor under fault identification are acquired, including the stator three-phase voltage, the rotor three-phase voltage, the stator three-phase current, the rotor three-phase current and the rotor rotating speed; 2) the three-phase signals are converted to a dq axis coordinate system, the motor parameters are acquired, then the three-phase signals are converted to an alphabeta axis coordinate system, the estimated stator current is acquired through an observer, and the estimated current difference is calculated and decomposed so that a fault severity factor xi is obtained; and 3) when the amplitude of the fault severity factor xi caused by the turn-to-turn short circuit fault reaches the fault early warning value, the stator winding turn-to-turn short circuit fault occurs on the offshore doubly fed motor under fault identification. Compared with the methods in the prior art, the offshore doubly fed motor stator winding turn-to-turn short circuit early fault identification method has the advantages that the fault phase can be reliably located and the robustness is high.

An antijam filter and method for filtering interference signals from signals received from the desired user in spatially multiplexed wireless communication systems. The antijam filter estimates the interference from known and unknown sources, and uses that estimate to filter the interference from the received signals. The filtered desired user signals are rendered for further signal processing using existing methods. The antijam filter and method are modular, with applicability to a wide range of wireless communication systems employing multiple antennas at the receiver.

A combined navigation method based on an INS (inertial navigation system) / GPS (global position system) / SAR (synthetic aperture radar) comprises steps as follows: an INS receiver, a GPS receiver and an SAR sensor are mounted in appropriate positions of an unmanned aerial vehicle in parallel; image matching is performed, and position navigation deviation of the INS is obtained and taken as an observed quantity to be input into a filter, and the observed quantity and other observed quantities are jointly filtered; GPS measuring deviation is obtained and taken as an observed quantity to be input into the filter, and the observed quantity and other observed quantities are jointly filtered; the filter integrates the measuring deviation from the GPS and the position navigation deviation, obtained through image matching, from the INS, and a navigation error estimated value is calculated. Topographic features are automatically and reliably extracted from an SAR image, a map image is formed in a digital map, and the SAR topographic features are automatically predicted; topographic deviation is accurately estimated and integrated; capture and matching are automatically initialized; the fault tolerance capability, the autonomy and the reliability of navigation are high.

Provided is a method for sorting a number of samples into an appropriate number of clusters according to their characteristics. Highly-correlated peaks are extracted from mass spectrum data obtained for the samples (S2). Using the extracted peaks, highly-correlated sample pairs are extracted (S3). While removing samples having low degrees of correlation, highly-correlated sample pairs are integrated to form core clusters (S4). Using singular peaks characterizing each core cluster, two or more core clusters are integrated to form clusters (S5-S7). These clusters include mixed clusters in which two or more clusters are mixed. Member determination formulae are created based on the singular peaks of each cluster (S8-S12). All samples, including those which have been excluded from the cluster determination process, are classified into clusters based on the member determination formulae (S14). The member determination formulae can also be used to assign a new sample to one of the cluster.

The invention discloses a goal detecting and a football video fine event detecting method based on the goal detecting. The steps of the goal detecting method are as following: (1) extracting a frame of color football video image; (2) the video image is straw hat transformed to extract the edge image; (3) searching for the section which fulfills definite threshold value in vertical direction neighborhood based on the edge image; (4) the section gained from the up step, the most longest sections are selected as alternative goal gatepost by Hofmann transformation; (5) whether the alternative goal gatepost in up step is goal can be determined by the second heuristic rule. The steps of the football video fine event detecting method based on the goal detecting includes: 1) goal detecting; 2) based on the detecting goal, combining the first heuristic rule to detect the fine event in the football video. The invention possesses advantages of accuracy, quick-speed and low false retrieval.

The present invention discloses an automatic segmentation method for retinal nerve fiber layer in OCT image of ocular fundus, comprising the following steps: A. determining the inner layer outline u(s) of the retinal region as u(s)=[x(s), y (s)], and the outer layer outline v(s) as v(s)=[x(s), y(s)]; B. describing the retinal region in local structure data p (x, y) mode, and constructing the energy function (the formula is shown above) based on the local structure data p (x, y) after constructing the level set function phi; and C. minimizing the energy function, calculating the boundary curvem as m= {(x, y) / phi (x, y) = 0} while phi (x, y) = 0, and defining the region between the boundary curve m(s) and the outer layer outline v(s) as the retinal nerve fiber layer region. According to the invention, retinal nerve fiber layer in OCT image of ocular fundus can be segmented reliably and accurately.

The present invention provides a novel spray pump inspection apparatus and method, which allow for accurate acceptability check of a spray pump even with an actuator attached to the spray pump, and are superior in inspection capability and operability to the prior art. The inventive spray apparatus is adapted to inspect a spray pump (20) which sprays a liquid from a container, and includes vibration sensors (2, 3) to be positioned adjacent the spray pump (20), and abnormality detection means (6) which detects spraying abnormality of the spray pump (20) on the basis of low frequency signal components of not higher than a predetermined frequency contained in detection signals generated by the vibration sensors (2, 3) when the spray pump (20) is actuated in air.

In an image processing apparatus for creating synthetic image information by embedding sub-information in an invisible state in main image information in a visible state, attention pixels in the main image information are set, a specific pixel block is created by assigning a first specific pixel to the attention pixel of a first color and a second specific pixel to the attention pixel of a second color, first key information is selected for a first value of the sub-information constituted by binary information and second key information is selected for a second value, color difference modulation processing is performed on the selected key information based on a predetermined color difference amount, and the color-difference-modulated key information is superposed on the specific pixel block to thereby create the synthetic image information in which the sub-information in an invisible state is embedded in the main image information.

What is disclosed is a system and method for extracting photoplethysmographic (PPG) signal (i.e., a cardiac signal) on a continuous basis from a time-series signals obtained from video images captured of a subject being monitored for cardiac function in a non-contact remote sensing environment involves the following. First, a time-series signal obtained from video images captured of a region of exposed skin where a photoplethysmographic (PPG) signal of a subject of interest can be registered. A sliding window is then used to define consecutive sequential segments of the time-series signal for processing. Each of the consecutive time-series signal segments is detrended such that low frequency variations and non-stationary components are removed. The detrended signals are processed to obtain, for each segment, a PPG signal. The PPG signal segments are then stitched together using a stitching method, as disclosed herein, to obtain a continuous PPG signal for the subject.

The invention belongs to the technical field of image processing and particularly relates to an infrared and visible image fusion method based on a saliency map and interest point convex hulls. The infrared and visible image fusion method comprises the following steps that firstly, saliency detection is conducted on an infrared image, so that a binarized saliency map is obtained; secondly, interest point detection is conducted on the infrared image; thirdly, free interest points are removed, and salient interest points are obtained; fourthly, convex hulls of the salient interest points are obtained, AND operation is conducted on the binarized saliency map and a convex hull image, so that a target area is obtained, and the remaining portion of the image is used as a background area; finally, different fusion rules are adopted for the target area and the background area respectively, and the infrared image and the visible image are fused. By the adoption of the infrared and visible image fusion method, a few of interest points on a background can be removed, the obtained convex hulls of the salient interest points are more approximate to a real target, and by means of the saliency map, the target area can be more accurately extracted; the fusion performance is easily, rapidly and effectively improved.

In an ultrasonic diagnostic apparatus capable of forming a three-dimensional ultrasonic image, an entire cavity portion of an organ can be displayed without any part being invisible. Three-dimensional ultrasonic image data obtained based on an ultrasonic wave transmitted and received with respect to an object organ is stored in a memory 20. With regard to the stored data, a brightness value of each voxel is binarized in a binarization processing section 24 using a predetermined threshold value. Then, the binarized brightness value is further inverted in a brightness value inverting section 26. Consequently, the cavity portion of the organ which has low brightness before inversion has high brightness, and the wall portion of the organ which has high brightness before inversion and which obstruct observation of the inner cavity portion has now low brightness. Thus, solid representation of the cavity portion to be observed can be obtained, thereby facilitating observation.

The invention provides a blood cell microscopic image classification method based on a regional confusion mechanism neural network. The method comprises the following steps: carrying out preprocessingoperation on a blood cell microscopic image for training; inputting the processed image data into training branches in a deep neural network framework; introducing a regional confusion mechanism in atraining stage; distributing a global structure of an input image, forcing a classifier to extract local fine features of a blood cell image, eliminating the noise interference introduced after confusion through an adversarial learning network, and performing modeling on structure information of the image through semantic correlation between the confused image and an original image; extracting the optimal parameters of the classifier through the branches, directly endowing the optimal parameters to the classification trunk network branches, and carrying out final classification prediction work.