104 results about "Spatial difference" patented technology

A radiation machine incorporating a diagnostic imaging system is disclosed. The invention provides a very stable design of the machine by supporting an inner gantry part, including a treatment and diagnostic radiation source and detector, by an outer gantry part at two support locations situated at opposite sides of a treatment volume in a patient to be irradiated. This stable gantry design provides a high rotation speed of the inner gantry part relative the outer gantry part around the target volume, which speed is adapted for the high resolution imaging system. Based on the obtained images, changes and developments in tumor tissue and misplacement of patient may be detected. The images may be compared to a reference image to detect any anatomical or spatial difference therebetween. Based on this comparison the settings of the radiation machine may be adapted accordingly.

The invention discloses an indoor positioning method based on distribution of channel state information (D-CSI), which comprises a training stage and a positioning stage. In the training stage, a fingerprint database is established by using fingerprint information of each reference point location. In the positioning stage, firstly fingerprint information of the location of a user to be positioned is calculated, then a distance value between the fingerprint information of the location of the user to be positioned and the fingerprint information of each reference point location is calculated by using KL distance, and the location of the user to be positioned is acquired by using a K-nearest neighbor algorithm. The indoor positioning method makes full use of the frequency diversity between different sub-bands and the diversity between different antennas, the time stability and the space difference of a location characteristic fingerprint can be enhanced, and thus the positioning accuracy is improved.

The invention discloses an urban building change detection method based on LiDAR point cloud spatial difference analysis. The method comprises the steps that 1, LiDAR point cloud data with different time phases are respectively preprocessed, and DSM and DTM of the different time phases are obtained through a linear interpolation algorithm; 2, two periods of the DSM obtained in the step 1 are subtracted to obtain an elevation difference model; 3, spatial difference analysis is carried out on the elevation difference model, and a candidate change area is extracted; 4, spatial features of a LiDAR point cloud are used for extracting direct features and elevation grain features; 5, building and vegetation classification is achieved; 6, superposition and overlay analysis is carried out on the candidate change area, and the building change attribute is determined. The advantages of the LiDAR data on three-dimensional representation of the building complex structure and the topological relation are fully achieved, and building three-dimensional change detection is carried out.

A device for detecting spatial differences in fluid level changes in a tissue of a patient may include a support structure for securing the device to a body part of the patient, a processing element operably connected to the support structure, a wireless networking interface operably connected to the support structure and in communication with the processing element and an external computing device via a network, a first transmission module operably connected to the support structure and in communication with the processing element, a second transmission module and a third transmission module operably connected to the support structure and in communication with the processing element. When activated, the first transmission module transmits a first time varying magnetic field through the tissue of the patient. The second and third transmission modules, which are spatially separated from one another, receive first and second versions, respectively, of the first time varying magnetic field.

The invention discloses a data acquisition and analysis method for river valley grassland degeneration conditions. The method specifically comprises the following steps of: NDVI data obtaining, DEM data obtaining, information processing, data conversion, vegetation coverage inversion, grassland degeneration grading, grassland degeneration cold / hot spot analysis, grassland degeneration temporal andspatial variation analysis, grassland degeneration cold / hot spot distribution and evolution, river valley grassland degeneration altitude differentiation, grassland coverage analysis and grassland degeneration factor analysis. Through a grassland degeneration grading map, the method is capable of integrally analyzing areas with obvious grassland degeneration grades in tested areas, so that the data analysis is more intuitional; cold / hot spot analysis indicates that the spatial difference between grassland degeneration and improvement is more obvious; through grassland coverage analysis, degeneration features of grasslands with different coverage grades can be quantitatively analyzed and expressed; and through analysis of climate temperatures, rainfall capacities and grazing conditions, the analysis of the grassland degeneration conditions is more correct.

The invention relates to a surfactant enhanced organic polluted soil electric-biological remediation method and a surfactant enhanced organic polluted soil electric-biological remediation device, which can effectively improve the efficiency of traditional electric-biological remediation of organic pollutants. The surfactant enhanced organic polluted soil electric-biological remediation method comprises the following steps: designing a cylindrical electrode matrix configuration of an annular anode on the outer side of a central cathode; filling a soil remediation system with biochar immobilized microorganisms along the inner side of the anode to form an annular biological PRB (Permeable Reactive Barrier), and adding a surfactant into remediated soil by adopting an electric injecting mode. According to the method, the difficult problems that the organic pollutant bio-availability is low, the remediation efficiency spatial difference is large, and the overall remediation efficiency is low in the traditional soil electric-biological combined remediation are solved; the method can be used for ex-situ remediation of organic polluted soil, and can also be used for in-situ remediation.

The invention relates to a permanent magnet system used in rotary magnetic refrigerator, wherein, the stator comprises a hollow cylinder permanent magnet and a magnetic conductive polar shoe; the hollow cylinder magnet is assembled symmetry around the central axle of the section of magnet via even permanent magnets; the magnetic direction of permanent magnet is decided by Halbach rotation theory; the magnetic conductive polar shoes are formed by two metals with better magnetic conductivity, while one side face is engaged with the wall of the chamber of permanent magnet, while another side is arc; two magnetic conductive polar shoes are contacted on the wall of chamber at the center of N and S polarities, with 180 degree spatial difference. The rotor comprises a rotary axle, a magnetic conductive iron corn and a magnetic medium; the rotary is cylinder; the iron corn is made from magnetic conductive magnet, as the cylinder with central hole or with cut-off two edges, sheathing the rotary axle while the rotary axle is at the center; two magnetic mediums are mounted on two outer arc faces of magnetic conductive iron corn, while the spatial positions are 180 degree different. The invention can be used as rotational permanent magnetic device.

An adaptive lossless data compression method for compression of color image data in a data processing system. The method includes comparing a plurality of components of a plurality of adjacent pixels in a digital image, calculating spatial differences between the plurality of adjacent pixels, encoding the spatial differences and recording the encoded spatial differences, formatting an image file representing the digital image into byte streams based on bit significance, and compressing, independently, the byte streams associated with each bit significance of the encoded spatial differences.

The invention discloses a projection-type capacitive touch screen system time domain noise reduction method by space differentiation. The method includes the steps that (1), a plurality of identical artificial circuit processing elements and relevant selection controllers are arranged inside a touch screen control chip; (2), a reference inducing line set of any target touch screen inducing line set to be processed in a touch screen inducing line array is selected according to space distribution; (3), identical imitation processors are used for driving and reading a target sensor and a reference sensor simultanously; (4), information of the target sensor and the reference sensor is judged; (5), the steps of (2), (3) and (4) are repeated until all target inducing lines of the touch screen are processed to finish one frame; (6) according to the distribution of status values of the inducing lines of the frame, finger touch points are calculated and judged, and time or space misinformation touch points are eliminated according to former frame information; and (7), according to the state of a current frame, the step (2) is returned or other operation is performed. According to the projection-type capacitive touch screen system time domain noise reduction method by the space differentiation, the system performance can be effectively improved, and the power consumption is reduced.

The invention provides raster scanning for depth detection. Techniques are provided for determining distance to an object in a depth camera's field of view. The techniques may include raster scanning light over the object and detecting reflected light from the object. One or more distances to the object may be determined based on the reflected image. A 3D mapping of the object may be generated. The distance(s) to the object may be determined based on times-of-flight between transmitting the light from a light source in the camera to receiving the reflected image from the object. Raster scanning the light may include raster scanning a pattern into the field of view. Determining the distance(s) to the object may include determining spatial differences between a reflected image of the pattern that is received at the camera and a reference pattern.

A motion path search device includes a motion space identification unit which identifies, as first spaces, three-dimensional spaces passed through by a movable part in direct teaching operations performed by an operator, and a spatial difference calculation unit that calculates a first differential space that is a part of one of the first spaces identified as a result of one of the direct teaching operations and that has no overlap with another of the first spaces identified as a result of another of the direct teaching operations that precedes the one of the direct teaching operations. A feedback unit provides the operator with information regarding the first differential space, and a path search unit searches for a motion path of the movable part within a first accessible space resulting from combining the first spaces after the direct teaching operations.

The invention discloses a wireless sensor network-oriented fault-tolerance event boundary detection method. The method comprises the following steps: detecting a failure node and correcting the measurement value based on a weighted median failure node correction method, and judging whether the node is an event boundary node based on an event boundary node judgment method for a normal vector. The failure node correction method makes preparations for the event boundary node judgment method, and the detection precision of the event boundary node is improved. The problem of the spatial differences of the sensing information of adjacent nodes in the event boundary area is solved, the event boundary is determined by utilizing the point, and the detection precision of the event boundary node is improved; by employing a distributed detection method, the method has high fault tolerance, the judgment result is uploaded on the event boundary node only, the energy consumption of the sensor network is reduced, and the life cycle of the network is prolonged; and moreover, the event boundary can be detected, the event spreading direction is determined, and scientific basis is provided for formulating rescue measures for a decision maker.

The invention discloses a medical image registration algorithm based on a convolutional neural network. The algorithm specifically comprises the following steps: data acquisition and preprocessing; Making a neural network training data set; Training a neural network; Performing coarse registration on the neural network model; And fine registration is carried out based on a gray value registrationalgorithm. According to the invention, the convolutional neural network can be skillfully combined with the traditional gray value-based registration algorithm; The invention discloses a convolutionalneural network elimination method in medical image processing. the complete labeled input sample is lacked; Training sample limitation and other problems, the spatial difference between a group of input fixed images and floating images is quickly calculated; Meanwhile, a neural network model rapidly obtains the spatial difference between the input images to be registered, the large spatial difference is reduced, the situation that a local optimal solution can be obtained in the optimization iteration process based on a gray value registration algorithm is avoided, and therefore the spatial difference between the two images to be registered can be rapidly and accurately calculated.

The invention discloses a terminal difference eliminating method in an indoor positioning technology based on signal intensity. First, in an offline stage, a positioning region is divided into grids and a rectangular coordinate system is built, signal intensity and position coordinates collected at sampling points are obtained, equalization processing is performed, and a position fingerprint database is generated; then, in a positioning stage, signal intensity information of an actual positioning position is collected, and is preprocessed; Pearson similarity between actual collected data and position fingerprint database data is calculated, and is utilized to update the database; and finally, the preprocessed signal intensity information corresponding to the actual position is matched with the updated database, the sampling point with relatively small distance is selected, and the position coordinates of the sampling point are utilized to estimate the positioning position. The terminal difference eliminating method provided by the invention effectively reduces adverse effects caused to a positioning result by difference of different terminal equipment in received signal intensity, improves the degree of accuracy of indoor positioning, and has relatively high practical application value.

An embodiment of the invention discloses a precipitation estimation method and device. The method comprises the following steps: according to PPI scanning data of a Doppler weather radar, determiningreflectivity factor intensity data; according to a preset reflectivity factor intensity conversion relation, converting the reflectivity factor intensity data into target reflectivity factor intensitydata, wherein the reflectivity factor intensity conversion relation is determined based on the temporal and spatial difference between the scanning data of the Doppler weather radar and detection data of a raindrop spectrometer; based on a target ZI relation, determining precipitation intensity data corresponding to the target reflectivity factor intensity data; and according to the precipitationintensity data, determining accumulated rainfall amount within a preset estimation time period. The method can effectively ensure accuracy of precipitation estimation.

The present application relates to a neural network training method, an apparatus, a computer readable storage medium and a computer device. The method includes: acquiring a training sample set, wherein each training sample in the training sample set has a corresponding standard tag; the training samples in the training sample set being inputted into the neural network model, wherein the neural network model includes a plurality of attention networks; the training samples being respectively mapped to a plurality of different subspaces, wherein each subspace includes a corresponding request vector sequence, a key vector sequence and a value vector sequence; the neural network model being used to calculate the spatial difference between each subspace; the output similarity being calculated according to the output of the neural network model and the standard label corresponding to each training sample; according to the spatial difference degree and output similarity degree, the parametersof neural network model being adjusted until the convergence condition is satisfied, and the target neural network model being obtained. The scheme provided by the present application can improve theaccuracy of the output result of the neural network model.

The invention provides an isolated network operation under-frequency load shedding parameter setting method and system. The method includes the steps of acquiring relevant data in a power system, utilizing a platform of an electromechanical transient simulation program for simulating to obtain system speed deviation and mechanical power change when an isolated network is formed, extracting generator dynamic frequency adjustment effect coefficients, load adjustment effect coefficients and system frequency adjustment effect coefficients, and calculating a load shedding value of corresponding setting action frequency of each generator in the isolated network and an introduced restoration-level under-frequency load shedding value. In the whole under-frequency load shedding parameter setting process, dynamic frequency differences among regional power networks due to difference of power network structures are considered comprehensively, spatial differences of dynamic frequency characteristics are reflected, results obtained via calculation are accurate and high in reliability, an efficient and precise method is provided for under-frequency load shedding setting, an existing parameter setting method is enabled to be improved greatly, the method and the system are applicable to power networks in different power network structures and of multi-computer systems, application range is enlarged, and isolated network operation capability is enhanced.

The invention discloses a sparse modeling method and system of a header related transmission function based on spherical harmonic function. The method comprises the following steps: processing a to-be-measured header related transmission function to generate the minimum phase header related transmission function, and removing a minimum phase amplitude mean value in full-measurement direction to obtain the minimum phase header related transmission function with the minimum space difference; modeling the minimum phase header related transmission function with the minimum space difference to obtain a sparse spherical harmonic coefficient; and generating the full-spatial continuous header related transmission function according to the space direction through the sparse spherical harmonic coefficient interpolation. Therefore, the interpolation spectrum distortion degree of the full-spatial continuous HRTF is lowered, the computing complexity is lowered, and the required storage amount is small; the method can be conveniently applied to dynamically drawing environment in an actual virtual reality system without being limited by individual personality; the system has high robustness and can be conveniently applied to the actual environment.

The invention relates to scene motion correction in fused image systems. Techniques to capture and fuse short- and long-exposure images of a scene from a stabilized image capture device are disclosed. More particularly, the disclosed techniques use not only individual pixel differences between co-captured short- and long-exposure images, but also the spatial structure of occluded regions in the long-exposure images [e.g., areas of the long-exposure image(s) exhibiting blur due to scene object motion). A novel device used to represent this feature of the long-exposure image is a "spatial difference map." Spatial difference maps may be used to identify pixels in the short-and long-exposure images for fusion and, in one embodiment, may be used to identify pixels from the short-exposure image(s) to filter post-fusion so as to reduce visual discontinuities in the output image.

The invention provides a regional terrestrial ecosystem respiratory monitoring method based on remote sensing. The monitoring method comprises the following steps: S1, obtaining time series satellite remote sensing data within a region; S2, performing remote sensing retrieval to key parameters; S3, quantifying key physiological and ecological parameters of different vegetation forms based on land cover or land utilization data; S4, obtaining meteorological interpolation data of time series; S5, carrying out cloud removal to obtain vegetation growing season curve without noise impact; S6, determining the annual respiratory capacity of the regional terrestrial ecosystem. The method is based on the time series remote sensing data, considers spatial difference of the vegetation form, determines the ecosystem respiratory algorithm within the region, solves the problem that the regional terrestrial ecosystem respiratory monitoring only relies on meteorological data but is insufficient to express heterogeneous information of the land cover within large scale, improves the precision of regional scale ecosystem respiratory estimation, and accurately and quantitatively describes temporal dynamics of the respiration in different ecosystems.

The invention discloses a method for extracting exercise ability parameters represented by cerebral cortex hemoglobin information. The steps include: (1) a stroke patient performs a finger-nose and heel-to-knee exercise experiment: the healthy side and the affected side complete the movement of the upper and lower limbs successively, The patient autonomously controls the start and end of the exercise and the rest time between the two tasks; (2) According to the information of the hemoglobin concentration in the cerebral cortex recorded during the exercise and during the rest, analyze the cerebral cortex of the patient before and after recovery from a multi-band perspective The degree of dispersion of oxygenated hemoglobin concentration in each motor function area, as well as the change trend of active frequency bands with positive concentration values ​​and inhibitory frequency bands with negative concentration values; (3) find out the change parameters of brain hemoglobin information space differences and the activation and inhibition The characteristic parameters of the frequency band represent the strength of stroke patients' exercise ability.

The invention relates to the field of MIMO radar (multiple-input multiple-output radar) super-resolution direction finding algorithm, discloses an MIMO radar super-resolution direction finding algorithm of coherent signal sources under the color noise background, and particularly provides an improved spatial difference smoothing (ISDS) algorithm. Besides, a fast algorithm based on a propagation operator, i.e. a PM-ISDS algorithm, is also provided based on the ISDS algorithm. Theoretical analysis and simulation prove that the algorithm has extremely high color noise suppression capacity, and the estimate performance is better than that of the common spatial smoothing algorithm so that the algorithm has great array element saving and signal source overload capacity without performing characteristic value decomposition and has low computational burden.

The invention relates to a method for recognizing a spatial difference by utilizing a complex number fMRI (functional magnetic resonance imaging) space source phase, belonging to the technical field of biomedical signal processing. The method comprises the following steps of carrying out spatial ICA (independent component analysis) separation on complex number fMRI data, choosing an interesting ingredient, then performing phase correction and noise elimination to obtain the spatial source phase of the interesting ingredient, and finally, calculating through a variance homogeneity analysis anda variance difference coefficient so as to recognize the differences of SZs and HCs in the spatial source phase. Compared with widely applied amplitude data, the method utilizes the spatial source phase to recognize the spatial difference between a schizophrenia patient group and a healthy control group, and can display higher flexibility and reliability. For example, specific to complex number fMRI data of 82 testees in a quiescent condition, the spatial source phase is used for extracting differential voxel, which is increased by more than 122.95% in DMN, on the premise of not using FDR correction, and the differential voxel, which is extracted from the spatial source phase and can pass the FDR correction, is 69% more than the amplitude.

The invention discloses a space-ground bistatic differential interferometry baseline coordinate and deformation quantity measurement method. S satellites are adopted to emit signals to a base station and a measurement station, the measurement station is arranged at the position needing coordinate measurement or deformation quantity measurement, frequency mixing processing is carried out on phase positions of direct-wave signals and phase positions of intrinsic signals as well as phase positions of signals of the measurement station and the phase positions of the intrinsic signals in the base station, and the direct-wave signal phase position history and the measurement station signal phase position history are obtained; the spatial difference phase of a direct-wave azimuth signal and a measurement station azimuth signal is worked out; when coordinate measurement is carried out, a reference satellite is selected, intersatellite difference is carried out on the spatial difference phase between a navigation satellite and the reference satellite, an intersatellite difference equation set is obtained and compensated, and an estimated value of a baseline coordinate is obtained after resolution. When deformation quantity measurement is carried out, difference is carried out on the spatial difference phases of the adjacent time periods, a time differential equation set is obtained and compensated, and a deformation quantity coordinate is obtained after resolution. The method is high in precision, low in cost and successive in time.

The invention provides a simulation method for topotactic transformation of a wireless sensing network, wherein generalized Euclidean distance between two sensor nodes is taken as cluster statistic, cluster analysis is performed on wireless sensing network topotactic transformation and impact factors influencing the wireless sensing network topotactic transformation so as to obtain a clustering result, each cluster in the clustering result corresponds to one subzone of one cellular space, zonal switching rules are used for replacing uniform switching rules, and a standard grid partitioning method is adopted for obtaining an asynchronous cellular evolutionary rate. Therefore, space-time difference, spatial heterogeneity of evolution laws and spatial differentiation of evolutionary rate are considered during a wireless sensing network topotactic transformation process.

The invention discloses a regional carbon flux estimation method based on remote sensing data. A mesoscale meteorological model (WRF) is used to output results, to provide spatial information within atarget region range and required meteorological field data for a vegetation photosynthetic respiration model (VPRM). High-precision vegetation type data (SYNMAP with a resolution of 1 km) is extracted, to classify land use types in a target area; an enhanced vegetation index (EVI) and a land surface water index (LSWI) are obtained by inversion of medium-high-resolution remote sensing data (MODIS09A1); parameters such as the EVI and the LSWI are placed in a target area grid by a spatial difference method; for different regional characteristics, more than one year of historical observation datais used, and these parameters are optimized by using a light response equation (Michaelis-Menten); and finally, based on the data, the carbon flux calculation is performed on the target area using the VPRM model.

The invention belongs to the technical field of soil detection, and particularly relates to a yield-based soil fertility prediction method for constructing a geographic minimum data set. The method comprises the following steps of (1) collecting a soil sample; (2) detecting fertility index content of the sample; (3) performing analytic calculation of an Nemero single fertility index and a comprehensive fertility index for the detected index content in the step (2); (4) performing principal component analysis on the detected index content in the step (2) by utilizing data processing software SPSS, selecting high-factor load indexes in the principal component analysis, and entering the minimum data set; (5) performing standardization calculation on the data set in the step (4); and (6) for the standardized minimum data set in the step (5), calculating minimum data set fertility indexes. Based on an analysis result of the correlation between the minimum data set fertility indexes and theyield, the fertility indexes can predict the soil fertility; and the soil fertility prediction method can perform unified evaluation for the soil fertility of Camellia oleifera Abel. with relatively large spatial difference, and is wide in application range.

A block noise detector has a spatial difference calculator that calculates differences between values of adjacent pixels. A spatial difference comparator detects edges by comparing the calculated differences. Eight counters count edges detected at different groups of positions spaced eight pixels apart in each horizontal line. The maximum count and the group of positions at which it occurs are detected at the end of each horizontal line to detect block noise and the positions of the block boundaries. The block noise detector is small in size because it only has to count edges in one line at a time, and detects edges accurately by comparing the difference at a given position separately with differences to the left and differences to the right.

The invention provides a wind power prediction method considering the wake effect. The method is characterized by comprising the following steps that (1) spatial difference is performed on NWP wind speed data by adopting an inverse distance method according to spatial distribution consistency of wind speed so that wind speed (the expression is described in the specification) of x is obtained, wherein (the expression is described in the specification) x refers to spatial coordinates, x refers to the spatial coordinates of the sampling position i, u(x) refers to the wind speed data of the sampling position i, lambda refers to the weight of the sampling position i, and l refers to Euclidean distance; (2) height difference of wind speed is realize by using the law of wind vertical shear power so that wind speed v<2>=v<1>(h<2> / h<2>)<alpha> of height h<2> is obtained, wherein alpha is a vertical wind shear index, v(2) is wind speed of height h<2>, and v<1> is wind speed of height h<1>; (3) wind speed of an actual operation blower is obtained according to a wake model and blower position data; and (4) corresponding power of the blower is obtained according to the wind speed-power curve of the actual operation blower. The wake effect and the wind speed-power curve of the actual operation blower are fully considered so that accurate prediction of wind power can be realized.