33 results about "Inverse iteration" patented technology

The invention discloses a bilateral filtering de-noising method of point cloud data based on KDTree when a ground laser scanning technology is used to carry out measured object surface reconstruction. In a bilateral filtering algorithm, a scattered point cloud data point field is established through the KDTree so as to obtain a field point set of the data point. An inverse iteration method is used to calculate the field point so as to obtain a normal vector ni. A filtering function parameter and a filtering Gauss parameter are calculated so as to obtain a bilateral filtering power factor lambda. Finally, a new data point after the filtering can be obtained, wherein the new data point p'i=pi+ lambdani. The bilateral filtering method of the invention is used to filter the noise of the point cloud data. The method is simple and effective. An operation speed is fast. A characteristic can be maintained and simultaneously the noise can be removed. The method is suitable for processing the noise in a small scope.

The invention relates to a method for reconstructing a large-scale complex flyover 3D model by using airborne LiDAR data. The method includes the following steps: using inverse iteration mathematic morphological filtering and area information to extract flyover point cloud from airborne LiDAR data; in accordance with bridge floor connectivity, segmenting the flyover cloud point; adopting a central line vertical line scanning method to segment and extract a communicated bridge surface which has no bifurcation or intersection structures and has a width consistent width, acquiring a "constitutional unit"; an end place of the constitutional unit central line serving as a circular buffer area, detecting a shielding structure of the flyover through determination of point cloud height information within the buffer area; through steps of constitutional unit matching, 2D central line fitting and 3D curved surface fitting, acquiring a complete bridge surface 3D central line; and reconstructing a flyover 3D model in combination with bridge surface width information. Practice has proved that the method of the invention can effectively reconstruct the large-scale complex flyover 3D model, addresses shielding problem of the flyover point cloud, and the reconstructed 3D model has a higher correctness and completeness.

The invention relates to a tomography method of using the limb sounding data for inverting atmospheric ozone profiles. The method comprises the following steps: respectively calculating the intersections between the gaze vector and the atmospheric grid radial and vertical boundary and atmospheric layer horizontal boundary, merging two types of intersections, then calculating the distance between adjacent intersections to obtain intercept; applying the tomography method in a correlate equation about volume emissivity and radiance, using the square iterative reconstruction technology to obtain the inverse iteration model of the volume emissivity, calculating the volume emissivity; and finally using an oxozone photochemical model to connect the volume emissivity with the ozone number density, and selecting the Newton iteration method to invert the ozone profiles.

The invention provides a morphological analysis inverse iteration method for determining space structural lofting states of a cable-strut-beam system. The method includes: using a nonlinear finite element inverse iteration method with construction process considered, using an inactivating-activating unit method to positively simulate construction process influences based on assumption of the lofting similar state, using a morphological compensation method to inversely correct a lofting state geometrical configuration and pretension scheme, gradually astringing a positive tension analysis result of a lofting similar state to a preset design state through positive-inverse loop iteration, and finally obtaining a precise lofting state geometrical configuration and pretension control scheme.

A soft decision value output detector includes a plurality of maximum a posteriori (MAP) detectors. The MAP detectors are configured to simultaneously generate state metrics for portions of a sampled data sequence, and to generate soft decision values based on the generated state metrics. Each of the MAP detectors includes a first MAP unit that generates state metrics by a reverse iteration using first and second reverse Viterbi operators and a forward iteration using a first forward Viterbi operator through portions of the sampled data sequence, and a second MAP unit that generates state metrics by a reverse iteration using third and fourth reverse Viterbi operators and a forward iteration using a second forward Viterbi operator through portions of the sampled data sequence. The first forward Viterbi operator has a different convergence length than the first and second reverse Viterbi operators, and the second forward Viterbi operator has a different convergence length than the third and fourth reverse Viterbi operators. The first and second forward Viterbi operators may have twice the convergence length of first through fourth reverse Viterbi operators.

A method of determining at least one material property of at least one component of an electrochemical system (fully or partially completed) using a process to reduce a difference of a performance characteristic between a numerical simulation result of a physical model and an empirical result. The method includes providing an electrochemical cell using a thin film process and performing a plurality of tests on the electrochemical cell to identify one or more target performance characteristics of the electrochemical cell. The method includes performing a surrogate based analysis process and determining a plurality of outputs of the surrogate based analysis function and determines a value of the unknown material property.

The present invention discloses a Givens iteration based Prony analysis method for low frequency oscillation, and the analysis method adopts an iterative method to reduce the number of orders of a signal model, and improve numerical stability of calculating a characteristic equation coefficient to solve an equation set. The method comprises the following steps: reading measurement data after filtering; using a singular value decomposition method to calculate the actual number of orders of the signal model; using a Givens iterative method to calculate the characteristic equation coefficient; calculating frequency and an attenuation factor; and calculating amplitude and an initial phase. According to the method disclosed by the present invention, by using a Givens iterative Prony method to analyze low frequency oscillation, the number of orders of the signal model maybe the actual number of orders of the signal model during extended Prony analysis, so that the singular of a coefficient matrix for using the characteristic equation coefficient to solve the equation set is effectively avoided, and the numerical calculation stability is improved; and under conditions of the number of orders of the signal model is the actual number of orders of the signal model, the method disclosed by the present invention has a higher calculated result of low frequency oscillation information than the result calculated by using the conventional Prony method.

The invention provides a safety rate maximization synthesis method based on general inverse iteration in direction modulation, comprising the following steps of: before designing a useful signal beamforming vector and an artificial noise projection matrix, firstly initializing the two by using a leakage concept, then updating the artificial noise projection matrix by using a general power iterative (GPI), and synchronously updating the useful signal beam forming vector by the Rayleigh-Ritz method. In order to maximize the safety rate, an alternately iterative structure (AIS) is used in designing the useful signal beam forming vector and the artificial noise projection matrix, and the corresponding safety rate needs to be updated in time. Compared with the traditional direction modulationtechnology, the safety rate of the invention is greatly improved at a medium to high signal-to-noise ratio, a useful signal can be demodulated well in a desired direction and is difficult to recover in an undesired direction, thereby better improving the safety performance of the system.

The invention discloses a steel structure fire disaster temperature field inverse presumption method based on displacement forms. The method comprises the following steps that field investigation is conducted on a steel structure after a fire disaster, the structure is divided into different grids, the geometric center point of each grid is used as a displacement characteristic point, and displacement values of the displacement characteristic points are measured; a finite element calculation model is established; the established finite element calculating model is used for determining a temperature-displacement topological matrix between the temperature change of a structure rod piece in a single grid and displacement of the displacement characteristic points of the other grids; a temperature correction weight matrix is calculated according to the distance relationships between the displacement characteristic points; temperature field inverse iteration presumption is conducted. By means of the steel structure fire disaster temperature field inverse presumption method, temperature field distribution of the steel structure in the fire disaster can be accurately and quantitatively obtained and accurate input conditions is provided for finite element simulation of the steel structure after the fire disaster. The steel structure fire disaster temperature field inverse presumption method is high in result precision, has universality and has wide application prospects in the fields such as performance estimation, repair and reinforcement, disassembly scheme making of steel structures after fire disasters.

The embodiment of the invention provides equipment for identifying and controlling normal insertion and inverse insertion. The equipment comprises an interface male base, an interface female base, an inverse insertion recognition magnet, a Hall switch and a logic controller, wherein the Hall switch is connected with the logic controller; the logic controller is respectively connected with the interface male base and the interface female base; when the Hall switch does not detect magnetism, a high level signal is generated, so that the logic controller communicates a USB interface, connected with keys of a keyboard, with a channel of a CPU of a tablet PC and controls the USB Hub of the USB interface of a keyboard side to be communicated with a channel of the CPU of the tablet PC; and when the Hall switch detects the magnetism, a low level signal is generated, so that the logic controller disconnects the USB interface, connected with the keys of the keyboard, with the channel of the CPU of the tablet PC and controls the USB Hub of the USB interface of the keyboard side to be communicated with the channel of the CPU of the tablet PC. Therefore, identification and control on normal insertion and inverse insertion of a two-in-one computer are realized.

The invention provides an electric power system load flow calculation method based on hot start and a quasi-Newton method and relates to the technical field of electric power systems. The method comprises the following steps of firstly, establishing a linear power balance equation of a power system according to the structure and parameters of the power system, and obtaining an initial solution ofa bus node voltage; then determining a coefficient matrix M of quasi-Newtonian load flow calculation, and replacing inverse of a jacobian matrix in an iterative matrix equation of load flow calculation by using M to carry out power system load flow iterative calculation; introducing a relaxation factor into the coefficient matrix M, and searching an optimal value of the relaxation factor by utilizing a genetic algorithm; finally, calculating an initial coefficient matrix M0 according to the initial solution of the bus node voltage and the optimal value of the relaxation factor; and utilizing acoefficient matrix M to replace the inverse of the jacobian matrix in the iterative matrix equation of the Newton-Raphson method to carry out load flow calculation, carrying out load flow calculation, obtaining the voltage amplitude and a phase angle of a bus node of a power system, and obtaining the transmission power of each line.

The invention belongs to the technical field of structural topological optimization, and provides a nonlinear eigenvalue topological optimization method and system considering a frequency correlation material. The method comprises the steps of according to actual working conditions, dividing a structure into grids, adding boundary conditions, and through finite element analysis, obtaining a corresponding total stiffness matrix and a corresponding total mass matrix in the structure; constructing a non-linear eigenvalue equation based on the corresponding total stiffness matrix and the total mass matrix in the structure, and solving the non-linear eigenvalue equation by adopting a continuous asymptotic numerical method and an inverse iteration method to obtain a structural feature frequency and a corrected feature vector; and establishing a topological optimization model by taking the fundamental frequency maximization of the structure as a target and meeting the volume constraint as a constraint condition and combining the structural feature frequency and the corrected feature vector, inputting the material components containing the frequency correlation material structure into the model, and obtaining the material consumption meeting the requirement through topological optimization.

The invention discloses a single-layer plane cable net glass curtain wall self leveling construction method based on form finding analysis, which is characterized in that in the nonlinear limited element construction simulation analysis period, a nonlinear limited element inverse iteration method for determining the single-layer plane cable net curtain wall zero state is adopted for carrying out the form finding analysis, and the height difference value of each knot point on a vertical cable in the initial state and the design forming state is obtained through calculation and is used for guiding the in-site construction. In the in-site construction control period, through a method of drawing marking points, the position of each knot point (the position of cable clamps) in the initial state is determined according to the height difference value of each knot point on the vertical cable in the initial state and the design forming state obtained through the limited element construction simulation calculation, and then, the curtain wall actual dead weight effect is utilized for making all knot points automatically displace to the design forming state positions. The method disclosed by the invention has the advantages that a large amount of construction cost can be saved, the operability and the applicability are strong (the method is particularly applicable to strong wind or ultra-high curtain walls), the construction difficultly and the damage rate of glass in the construction process and the service period can be reduced, and the potential safety hazard is reduced.

The invention discloses a joint detection algorithm applied to a massive MIMO uplink, which constitutes a joint detection algorithm with two external large iterations and two internal small iterations, wherein the external large iterations are respectively information interaction of a decoder and a detector and information interaction of interference estimation and the detector, and the internal small iterations are respectively the internal iteration of the detector LMMSE-ISDIC algorithm and the iteration of the decoder. The algorithm fully utilizes the iterative structure of the decoder to construct two large iterative structures similar to the Turbo turbine, which improves the detection accuracy of the large-scale MIMO uplink. Compared with the traditional uplink detection, the joint detection can sufficiently use the information interaction of each module to promote each other and jointly improve the final detection accuracy.

The invention discloses a real-time online instrument verification and diagnosis method through a least square algorithm. The method comprises the following steps: S1, establishing a flow network model; S2, iterating field actual measurement data, and calculating and determining parameters in the model through a least square algorithm to enable the model to be available; S3, restarting the above steps regularly, and optimizing parameters; S4, verifying the sampled variables one by one by utilizing the model in a stable flow field state; S5, after the suspected failure point is eliminated, performing inverse iterative operation by using other data, and reversely deriving a theoretical calculation value of the suspected failure point; S6, eliminating process condition changes, performing comparative analysis on the actual instrument signal by using the theoretical calculation value, realizing verification and fault diagnosis, and determining a signal health level; and S7, recording a sampling signal and a calculation signal according to the measurement time, and giving an alarm and positioning a fault according to a deterministic fault diagnosis condition. Instrument faults can be found and reported early, results can be corrected intelligently, and work efficiency is improved.

A spacecraft attitude control system for maneuvering law singularity avoidance, comprising an attitude task management unit, an attitude controller, an attitude measuring unit, a gyro group maneuvering law unit, a frame angle position measuring unit, a control moment gyro group and a spacecraft. The gyro group maneuvering law unit calculates the frame angular rate of the control moment gyro group through the control moment gyro angular momentum table, zero motion algorithm and pseudo-inverse maneuvering law algorithm, and uses the angular rate value as the given signal of the control moment gyro group, In order to improve the control accuracy of spacecraft attitude. The present invention introduces a steering law design method based on the look-up table method to select the frame angular rate and the initial value of the frame angular position, realizes the precise torque output of the control moment gyroscope group, and avoids the pseudo-inverse maneuvering law calculation method to obtain the control moment gyroscope frame angular rate The singularity problem generated in the process avoids the "deadlock" problem that occurs when the zero-motion algorithm and the robust pseudo-inverse steering law are iteratively calculated.

The invention provides a morphological analysis inverse iteration method for determining space structural lofting states of a cable-strut-beam system. The method includes: using a nonlinear finite element inverse iteration method with construction process considered, using an inactivating-activating unit method to positively simulate construction process influences based on assumption of the lofting similar state, using a morphological compensation method to inversely correct a lofting state geometrical configuration and pretension scheme, gradually astringing a positive tension analysis result of a lofting similar state to a preset design state through positive-inverse loop iteration, and finally obtaining a precise lofting state geometrical configuration and pretension control scheme.

The invention provides a power system power flow calculation method based on hot start and quasi-Newton method, and relates to the technical field of power systems. This method first establishes the linear power balance equation of the power system according to the structure and parameters of the power system, and obtains the initial solution of the bus node voltage from it; then determines the coefficient matrix M of the quasi-Newton power flow calculation, and uses M instead of the Newton method for power flow calculation The inverse of the Jacobian matrix in the iterative matrix equation is used to iteratively calculate the power system power flow; at the same time, the relaxation factor is introduced into the coefficient matrix M, and the optimal value of the relaxation factor is found by using the genetic algorithm; finally, according to the initial solution of the bus node voltage and the relaxation factor The optimal value calculation initial coefficient matrix M 0 , and use the coefficient matrix M to replace the inverse of the Jacobian matrix in the iterative matrix equation of the power flow calculation, iteratively carry out the power flow calculation, and obtain the voltage amplitude and phase angle of the bus node of the power system, and then obtain the transmission of each line power.

The invention discloses a form finding method of a cable net structure, which specifically comprises the following steps of: obtaining a group of coordinates and internal force of a cable net by utilizing a classical force density method in a non-load state, taking the configuration as an initial form, solving node coordinates and internal force of the structure under the load by continuously correcting the internal force of the structure under the load effect, namely afeasiable form, and completing form finding and force finding work. The coordinates and the internal force of the initial state are determined through the classical force density method, and the force density method is good in convergence and high in efficiency; the initial form is approximate to the feasible form, and the partial inverse iteration method only corrects the internal force of the cable net structure, so that the probability of algorithm divergence is reduced; the method can be combined with existing large finite element analysis software (such as ANSYS, SAP2000 and the like), and has good universality.

The invention discloses a real-time online instrument verification and diagnosis method through an adaptive support vector machine algorithm. The method comprises the following steps: S1, establishinga flow network model; S2, iterating field actual measurement data, and calculating and determining parameters in the model through an adaptive support vector machine algorithm to enable the model tobe available; S3, restarting the above steps regularly, and optimizing parameters; S4, verifying the sampled variables one by one by utilizing the model in a stable flow field state; s5, after the suspected failure point is eliminated, performing inverse iterative operation by using other data, and reversely deriving a theoretical calculation value of the suspected failure point; s6, eliminating process condition changes, performing comparative analysis on the actual instrument signal by using the theoretical calculation value, realizing verification and fault diagnosis, and determining a signal health level; and S7, recording a sampling signal and a calculation signal according to the measurement time, and giving an alarm and positioning a fault according to a deterministic fault diagnosis condition. Instrument faults can be found and reported early, results can be corrected intelligently, and work efficiency is improved.

The invention belongs to the technical field of cable glass curtain wall construction, and specifically provides a method for tracking internal force and deformation during cable tensioning construction. S01: Calculate the initial strain required to meet the pre-applied force through an inverse iteration method, and then calculate the tension The actual internal force and actual displacement corresponding to the initial strain of the cable, the inverse iteration method includes the improved tension compensation iteration method; S02: After the initial strain value obtained by the previous iteration, the initial strain value is used as the initial value of the next cycle calculation. Strain value; S03: When the cycle reaches k times, if the difference between the actual internal force of the cable and the pre-applied force is less than the preset value, the cycle ends, and the stress value obtained by each calculation above is recorded corresponding to each tension stage. The actual internal force of the cable, where k is greater than 1. According to the target cable force of the cable at each stage, the corresponding internal force and deformation of the cable are calculated, which provides theoretical data and reference for construction, and improves the safety and reliability of the construction of the cable glass curtain wall.

The invention discloses a network coding-based scalable video stream encryption method. The method specifically comprises the following steps of first, pre-coding video stream data, so as to generate an image group sequence; then performing randomization on some data blocks of each layer in a plaintext message in each image group; next, performing linear randomization separately on the highest layer (the lowest transmission priority layer) of data, performing iterative transformation layer by layer according to a sequence from the second highest layer (the second lowest transmission priority layer) to a basic layer, and performing the same random linear combination on each data layer and data corresponding to an adjacent low priority layer simultaneously; and according to video quality subscription levels, decoding by each receiving terminal by using a layer-by-layer inverse iteration method. Through adoption of the method, quantitative security is realized in video stream security incremental encoding, further, in applications with different security demands, data confidential degree and video transmission coding and decoding flexibility are realized, the computing complexity is low, and the encryption efficiency is high.

The invention discloses a nuclear power plant non point source radiation source intensity backstepping method and a non point source radiation source intensity backstepping system. In the nuclear power plant non point source radiation source intensity backstepping method, the dosage rate of a plurality of positions is obtained through detectors, normalized radiation source intensity is dispersed in space, the optical distance is worked out by means of a ray tracing method, the coefficient of the equation set is calculated by combining information of materials and build-up factors and the like, the source intensity is backstepped, then the dosage rate of the detector positions is calculated, the measured value and the calculated value are subjected to linear-regression analysis, key parameters of the standard deviation, the slope, the intercept and the like are calculated, and furthermore the quality factor is calculated to evaluate the acceptance level of each calculating result . a weighted iteration method is provided at the same time, the error introduced by the detector with relatively-high uncertainty is reduced, the above steps are repeated for many times by means of an iteration manner until the quality factor reaches a preset value, and the expected radiation source intensity information is obtained.

The invention discloses a simple radar multi-target parameter extraction method. In the method, D is equal to three targets, when the number of targets is greater than 3, equations similar to equations (3) and (4) can be written in an imitating manner, but only the expression is relatively lengthy. The simple radar multi-target parameter extraction method specifically comprises the following steps: 1), estimating initial parameters of a signal direction, wherein when i ranges from 1 to D, D represents the sequence number of signals and is supposed to be equal to 3, if i is equal to 1, a formula shown in the description and another formula shown in the description are calculated so as to obtain an estimated target direction parameter initial value shown in the description, and i ranges from 1 to 3; 2), performing main iterative circulation, estimating a parameter shown in the description according to the initial parameters obtained in the step 1), thereby obtaining precise estimation on i, wherein i ranges from 1 to 3; 3), for the precise estimation on the value as shown in the description obtained in the step 2), calculating another two formulas shown in the description so as to obtain estimation on three target waveform parameters according to formula (4) and (8) shown in the specification, thereby providing parameter basis on target positioning and waveform identification, wherein i ranges from 1 to 3; when the number of the targets is greater than or equal to 3, writing a corresponding matrix shown in the description, Qi and expression of a projection matrix operator Pak,i according to existing expression such as P <A2-3> and matrix inversion iterative calculation relationship shown in the description. Therefore, the calculation complexity degree is substantially reduced, and the inversion errors can be avoided.

The invention relates to a method for reconstructing a large-scale complex flyover 3D model by using airborne LiDAR data. The method includes the following steps: using inverse iteration mathematic morphological filtering and area information to extract flyover point cloud from airborne LiDAR data; in accordance with bridge floor connectivity, segmenting the flyover cloud point; adopting a central line vertical line scanning method to segment and extract a communicated bridge surface which has no bifurcation or intersection structures and has a width consistent width, acquiring a "constitutional unit"; an end place of the constitutional unit central line serving as a circular buffer area, detecting a shielding structure of the flyover through determination of point cloud height information within the buffer area; through steps of constitutional unit matching, 2D central line fitting and 3D curved surface fitting, acquiring a complete bridge surface 3D central line; and reconstructing a flyover 3D model in combination with bridge surface width information. Practice has proved that the method of the invention can effectively reconstruct the large-scale complex flyover 3D model, addresses shielding problem of the flyover point cloud, and the reconstructed 3D model has a higher correctness and completeness.

The invention discloses a spectrum inverse auction bidding method based on beam forming and power distribution. The spectrum inverse auction bidding method is characterized by comprising the following steps of: S1, establishing an inverse auction model; S2, carrying out beam forming and power distribution by a third-party base station; S3, establishing a bidding function of an owner of the third-party base station; and S4, establishing a target function of combining precoding with power distribution to carry out bidding design. According to the spectrum inverse auction bidding method disclosed by the invention, bidding reasonability of the owner of the third-party base station in the spectrum inverse auction model shared by the cellular network traffic can be well ensured, so that real value of all idle bands of the owner of the third-party base station is truthfully reflected; the spectrum inverse auction bidding method is easy to implement and convenient to expand; and bidding and a throughput of a third-party network are linked to establish the bidding function. Moreover, by utilizing beam forming and power distribution, the throughput of the third-party network in the inverse auction model is maximized, and the bidding function is optimized, so that the characteristic of truth of inverse auction is ensured.

The invention discloses an instant online instrument verification and diagnosis method through an optimal support vector machine algorithm. The method comprises the following steps: S1, establishing aflow network model; S2, iterating field actual measurement data, and calculating and determining parameters in the model through an optimal support vector machine algorithm to enable the model to beavailable; S3, restarting the above steps regularly, and optimizing parameters; S4, verifying the sampled variables one by one by utilizing the model in a stable flow field state; S5, after the suspected failure point is eliminated, performing inverse iterative operation by using other data, and reversely deriving a theoretical calculation value of the suspected failure point; s6, eliminating process condition changes, performing comparative analysis on the actual instrument signal by using the theoretical calculation value, realizing verification and fault diagnosis, and determining a signalhealth level; and S7, recording a sampling signal and a calculation signal according to the measurement time, and giving an alarm and positioning a fault according to a deterministic fault diagnosis condition. Instrument faults can be found and reported early, results can be corrected intelligently, and work efficiency is improved.

The invention discloses a bilateral filtering de-noising method of point cloud data based on KDTree when a ground laser scanning technology is used to carry out measured object surface reconstruction. In a bilateral filtering algorithm, a scattered point cloud data point field is established through the KDTree so as to obtain a field point set of the data point. An inverse iteration method is used to calculate the field point so as to obtain a normal vector ni. A filtering function parameter and a filtering Gauss parameter are calculated so as to obtain a bilateral filtering power factor lambda. Finally, a new data point after the filtering can be obtained, wherein the new data point p'i=pi+ lambdani. The bilateral filtering method of the invention is used to filter the noise of the point cloud data. The method is simple and effective. An operation speed is fast. A characteristic can be maintained and simultaneously the noise can be removed. The method is suitable for processing the noise in a small scope.

The invention discloses a real-time online instrument verification and diagnosis method through an RBF particle swarm optimization algorithm. The method comprises the following steps: S1, establishinga flow network model; S2, iterating field actual measurement data, and calculating and determining parameters in the model through an RBF particle swarm optimization algorithm to enable the model tobe available; S3, restarting the above steps regularly, and optimizing parameters; S4, verifying the sampled variables one by one by utilizing the model in a stable flow field state; S5, after the suspected failure point is eliminated, performing inverse iterative operation by using other data, and reversely deriving a theoretical calculation value of the suspected failure point; S6, eliminating process condition changes, performing comparative analysis on the actual instrument signal by using the theoretical calculation value, realizing verification and fault diagnosis, and determining a signal health level; and S7, recording a sampling signal and a calculation signal according to the measurement time, and giving an alarm and positioning a fault according to a deterministic fault diagnosis condition. Instrument faults can be found and reported early, results can be corrected intelligently, and work efficiency is improved.