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148results about How to "Avoid training" patented technology
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Screen protector
InactiveUS7070837B2Prevents orMinimize formationLiquid crystal compositionsAdhesive processesRefractive indexEngineering
A plastic film screen protector that prevents interference patterns from arising when the film touches the screen is described. The advantages are accomplished by the film having a slightly roughened surface so that the majority of the film facing an electronic device screen does not substantially touch the screen. These physical aberrations prevent Newton ring interference patterns and spots caused by refractive index differences between air and the film material.
Owner:ROSS MARK
Method of constructing data classifiers and classifiers constructed according to the method
InactiveUS6622134B1Efficient constructionAvoid trainingDigital computer detailsCharacter and pattern recognitionOvertrainingAlgorithm
A method of constructing data classifiers in cases where the number of features is much larger than the number of training examples and it is critical to avoid overtraining, is particularly useful in recognizing computer objects containing or likely to contain a computer virus. The method provides a novel way of tolerating imperfectly classifiable data, of learning in time polynomial in the size of the input data, and of avoiding overtraining. Training is performed by constructing and solving a linear program (LP) or integer program (IP).
Owner:TREND MICRO INC
Face recognition method based on aggregate loss deep metric learning
InactiveCN107103281AAvoid hard case miningAvoid trainingCharacter and pattern recognitionNeural learning methodsNetwork modelMethod of undetermined coefficients
The invention discloses a face recognition method based on aggregate loss deep metric learning. The method comprises the steps of 1), preprocessing a training image; 2), performing pre-training on a deep convolutional neural network by means of the preprocessed image, using a softmax loss as a loss function and introducing key point pooling technology; 3), inputting all training images into a pre-trained model, and calculating the initial kind center of each kind; 4), performing fine adjustment on the pre-trained model by means of the aggregate loss, aggregating the samples of the same kind to the kind center through iteratively updating a network parameter and the kind center, and simultaneously increasing distances between different kind centers, thereby learning robust discriminative face characteristic expression; and 5), in application, performing preprocessing on the input image, and respectively inputting the input image into the trained network model for extracting characteristic expression, and realizing face recognition through calculating similarity between different faces. The face recognition method can realize relatively high face recognition accuracy just through training small mass of data.
Owner:SUN YAT SEN UNIV
Node indoor locating method based on wireless signal strength in wireless sensor network
InactiveCN101247650AReduce communication consumptionSmall amount of calculationPosition fixationRadio/inductive link selection arrangementsWireless mesh networkAnchor point
The present invention belongs to node self-localization field in large-scale wireless sensor network, and discloses a node indoor localization method based on wireless signal intensity, which main includes: getting relationship curve of signal intensity and distance, and putting forward concept of effective wireless signal intensity (Effective RSS, ERSS); obtaining coordinates of target node by selecting localization arithmetic (ERSS filter + maximum likelihood estimation, triangle localization, approximate location estimation) according with anchor point amount through distance between anchor point and target by training RSS curve; providing alerting service by using physics coordinate, providing navigation service according with route arithmetic and address chain by using sign coordinate (for example in hall). Precisely localization of indoor target can be realized in condition of low-cost, simple initial configuration, and a plurality of services based on location can also be provided.
Owner:JIAXING WIRELESS SENSOR NETWORKS CENT CAS
Exercise apparatuse with temperature variable handle assembly
InactiveUS20180056111A1OptimizationIncrease body temperatureMuscle exercising devicesMovement coordination devicesCelsius DegreeEngineering
An exercise apparatus includes a motion mechanism and a handle assembly. The motion mechanism is provided for a user to perform exercise. The handle assembly has at least one grip portion for being held by the user during exercising. Specifically, the grip portion has a temperature variable area thereon. The temperature of the temperature variable area could be controlled to rise to a suitable temperature that the hand of the user can feel warm, for example, a temperature between 38 and 50 degrees Celsius. The temperature of the temperature variable area could also be controlled to reduce to a suitable temperature that the hand of the user can feel cool, for example, a temperature between 20 and 36 degrees Celsius. The temperature of the temperature variable area could be directly controlled by the user or automatically changed according to the exercise status of the user.
Owner:JOHNSON HEALTH TECH
Product packaging surface defect detection and classification method based on machine vision
InactiveCN106204618AAvoid human interferenceAvoid trainingImage enhancementImage analysisColor imageFeature extraction
The invention discloses a product packaging surface defect detection and classification method based on machine vision. The method comprises the steps of 1, acquiring a high-definition color image of defect-free product packaging, making the high-definition color image into a standard image, conducting real-time shooting with a camera, conducting online acquisition of a high-definition color image of product packaging to be detected, and making the high-definition color image as an image to be detected; 2, conducting image matching on the image to be detected and the standard image based on SURF algorithm; 3, conducting difference image operation on the two images matched in step 2 to obtain a defective image; 4, conducting feature extraction on the defective image to obtain the geometrical features and color features of the defective image; 5, classifying product packaging surface defects by means of RBF neural network algorithm. Automatic defect detection and classification are conducted by means of a machine vision system, human factor interference can be avoided, labor cost is reduced greatly, and then huge hidden cost caused by training and management when artificial detection is adopted is avoided.
Owner:NANJING WENCAI SCI & TECH
Mobile shredder
A mobile shredder comprises a truck having a truck body defining an enclosure and including a partition in the enclosure that divides a storage volume from the remainder of the enclosure for storage of shredded material in the storage volume, a single-shaft rotary shredder mounted in the enclosure outside the storage volume, the rotary shredder comprising a rotor having cutters rigidly mounted thereon, a bin lift and dump mechanism operable to transport material to be shredded from outside to inside the enclosure so as to deliver material to the rotary shredder, and a discharge conveyor operable to transport shredded material from the rotary shredder through the partition to the storage volume. The floor of the storage volume can comprise a walking floor, and the enclosure can have rear doors that are openable to allow shredded material to be discharged through the open rear doors when the walking floor is operated.
Owner:VECOPLAN
Unsupervised domain adaptation method based on adversarial learning loss function
ActiveCN110837850AEfficiently match feature distributionsMatch feature distributionCharacter and pattern recognitionFeature extractionA domain
The invention discloses an unsupervised domain adaptation method based on an adversarial learning loss function, and the method comprises the steps: (1), generating a high-level feature of a source domain image through a feature extraction network G, carrying out the cross entropy loss with a real label through a classifier C, generating a confusion matrix through a domain discriminator D, and correcting a pseudo label into the real label; and (2) generating high-level features of the target domain image through a feature extraction network G, generating pseudo tags through a classifier C, generating a confusion matrix of the high-level features through a domain discriminator D, and correcting the pseudo tags to be in opposite distribution. (3) confronting and optimizing the loss functionby a feature generator and a discriminator. In addition, for the confusion matrix on the target domain, a correction label is generated and serves as a label of the target domain, and the classifier is optimized. By utilizing the method and the device, the noise of the pseudo tag can be corrected in unsupervised domain adaptation, and the distribution difference between the domains is matched, sothat the classification precision of the target domain is improved.
Owner:ZHEJIANG UNIV
Biofeedback training system and method and intelligent terminal
InactiveCN105797257AEffective guidanceAvoid trainingSensorsMeasuring/recording heart/pulse rateBiofeedback trainingResonance
The invention discloses a biofeedback training system which comprises a biological information feedback device and an intelligent terminal. The biological information feedback device at least comprises sensors used for collecting biological information representing a body state; the intelligent terminal comprises a signal receiving unit, an evaluation and training feedback unit and a display unit; the signal receiving unit receives the biological information representing the body state in real time; the evaluation and training feedback unit generating evaluation feedback information according to the biological information received within a period of time, and the evaluation feedback information is used for showing a synchronous trend of the heart rate and respiratory frequency within the period of time; the display unit at least continuously supplies the evaluation feedback information to a user and guides the user to change the biological information by adjusting the body state till the heart rate and the respiratory frequency reach resonance. The biofeedback training system can obtain the biological information and the evaluation feedback information in real time and effectively conduct real-time training guidance on the user, and the training effectiveness and a good using feeling of the user can be improved to a certain extent.
Owner:包磊
Mobile shredder
Owner:VECOPLAN
Transverse federation and longitudinal federation combination method and device, equipment and medium
The invention discloses a transverse federation and longitudinal federation combination method and device, equipment and a medium. The transverse federation and longitudinal federation combination method comprises the steps of obtaining available public information, inputting the available public information into a preset longitudinal federation service party; obtaining vector information, and training a longitudinal federation model of the preset longitudinal federation service party based on the vector information, updating the network weight of each preset reinforcement learning model, periodically inputting each updated preset reinforcement learning model into a preset transverse federation server, and iteratively updating each updated preset reinforcement learning model. The technicalproblem of high resource consumption of a computing system of a reinforcement learning model in the prior art is solved.
Owner:WEBANK (CHINA)
Automated pruning or harvesting system for complex morphology foliage
Method and apparatus for automated operations, such as pruning, harvesting, spraying and / or maintenance, on plants, and particularly plants with foliage having features on many length scales or a wide spectrum of length scales, such as female flower buds of the marijuana plant. The invention utilizes a convolutional neural network for image segmentation classification and / or the determination of features. The foliage is imaged stereoscopically to produce a three-dimensional surface image, a first neural network determines regions to be operated on, and a second neural network determines how an operation tool operates on the foliage. For pruning of resinous foliage the cutting tool is heated or cooled to avoid having the resins make the cutting tool inoperable.
Owner:BURDEN KEITH CHARLES
Color image color meaning classification method of based on fully convolutional network
InactiveCN107016415AReduce network sizeAvoid Huge Parameter TrainingImage enhancementImage analysisClassification resultConvolution
The invention discloses a color image color meaning classification method of based on a fully convolutional network. The method includes 1. constructing a fully convolutional network; 2 obtaining a color image data set with pixel level labeling; 3. training the fully convolutional network by means of the color image data set to obtain the feature model for performing pixel level color meaning classification on color images in any size; 4. performing the pixel level color meaning classification on any color image by the feature model to evaluate the classification precision of the feature model; and 5. optimizing the network classification result by a whole connection condition random field method to obtain the color class label of each pixel in the image, and transforming the color class labels into the corresponding color spaces to display the pixel level color meaning classification result according to the mapping relationship between the class labels and the color spaces. The method provided can realize the pixel level color meaning classification of the color images, and effectively improves the classification precision of the color image color meaning in the complex and changeable environment.
Owner:HEFEI UNIV OF TECH
Pedestrian re-identification method and apparatus
ActiveCN107346409AAvoid trainingReduce testing costsBiometric pattern recognitionSaliency mapReference image
Embodiments of the invention disclose a pedestrian re-identification method and apparatus. The method comprises the steps of obtaining a target image and a reference image; detecting a first local salient feature and a second local salient feature, wherein the first local salient feature is a local salient feature of the target image on a target region, and the second local salient feature is a local salient feature of the reference image on the target region; and calculating the similarity between the first local salient feature and the second local salient feature, wherein the target region is located in any region on a pedestrian body, and the process of detecting the local salient features comprises the steps of obtaining a salience map in the target region; performing binarization on the salience map of the target region to generate a binary image; and extracting a connected part set in the target region from the binary image, and determining the local salient features, wherein the local salient features include connected parts meeting a preset condition in the connected part set.
Owner:HUAWEI TECH CO LTD
K-means and deep learning-based image classification algorithm
InactiveCN106845528AAvoid trainingSimplify the training processCharacter and pattern recognitionImaging FeatureHigh dimensional
The invention discloses a K-means and deep learning-based image classification algorithm. The algorithm comprises the steps of 1) taking untagged images as input images, and randomly extracting image blocks to form an untagged image set of the untagged images same in size; 2) extracting a primary optimal clustering center by adopting a K-means algorithm; 3) constructing a feature mapping function, and extracting image features of the untagged image set; 4) performing pooling operation and normalization processing; 5) extracting a secondary optimal clustering center by adopting the K-means algorithm, extracting final image features by adopting convolution operation, and performing standardization processing on the final image features; and 6) classifying the final image features subjected to the standardization processing through a sorter. The algorithm has the advantages of simplicity, high efficiency, few training parameters and the like, and has a very good effect for classification of massive high-dimensional images; and the input images are preprocessed, so that the effects of improving the image classification effect and enhancing the classification precision are achieved.
Owner:HUBEI UNIV OF TECH
Method and devices for driving a damper
ActiveUS20100253270A1Total current dropAvoid damageProgramme controlMotor/generator/converter stoppersDriving currentRest position
An actuator (1) comprises an electrical motor (10) for driving a damper (3) from a rest position to a stalled position. The damper (3) is biased toward the rest position with at least one spring. A control module (2) is configured to supply, upon activation of the actuator (1), a drive current to the electrical motor (10) for driving the damper (3) from the rest position to the stalled position against a bias force produced by the spring. The control module (2) is further configured to reduce the drive current to a lower level for maintaining the damper (3) in the stalled position when a defined duration of time has elapsed since activation of the actuator (1). Damages to the electrical motor (10) and / or gear trains can be avoided without having to provide any circuitry or sensory equipment for measuring the drive current.
Owner:BELIMO HOLDING AG
Multi-task named entity recognition method combining text classification
ActiveCN111209738AImprove the accuracy of named entity recognitionGood effectCharacter and pattern recognitionNatural language data processingConditional random fieldFeature vector
The invention discloses a multi-task named entity recognition method combining text classification. The method comprises the following steps: (1) constructing a text classifier by using a convolutional neural network, and measuring the similarity of texts; (2) selecting a proper threshold value, and for the data set of the auxiliary task, determining whether the data set participates in updating of sharing layer parameters or not according to comparison of a text classification result and the threshold value; (3) cascading the character vector of the text with a pre-trained word vector to serve as an input feature vector; (4) in a sharing layer, modeling the input feature vector of each word in the sentence by using bidirectional LSTM, and learning public features of each task; and (5) sequentially training each task in the task layer, transmitting the output of the sharing layer to a bidirectional LSTM neural network in the main task private layer or the auxiliary task private layer,performing label decoding on the whole sentence by utilizing a linear chain conditional random field, and labeling entities in the sentence. Experiments are carried out on data sets in multiple biomedical fields, so that the named entity recognition effect of a specific field with difficult corpus acquisition and high labeling cost can be effectively improved.
Owner:ZHEJIANG UNIV
System and method for identifying voice prints based on phoneme information
ActiveCN106448685ASegmentation effect advantageAvoid trainingSpeech analysisMandarin speech recognitionNeural network classifier
The invention relates to a system and a method for identifying voice prints based on phoneme information. The system comprises a phoneme forced aligning module, a phoneme relevance model creating module and a neural network classifier module, wherein the phoneme forced aligning module is based on a Chinese mandarin voice identifier; the neural network classifier module is based on a dropout strategy. The method comprises the following steps of defining sixteen phoneme types of Chinese mandarin numeric string voice prints, and digitally utilizing each piece of pronunciation type information of a numeric string; according to the Chinese mandarin voice identifier, using a viterbi forced aligning algorithm to obtain the phoneme boundary of the text content of each numeric string; using a text irrelevance algorithm to establish a phoneme relevance model; calculating the phoneme relevance model, so as to obtain a fraction vector. The system and the method have the advantages that the functions of division of phoneme information, modeling of phonemes and analysis of distinguishing capability of the phoneme relevance model are realized, the neural network training method based on the dropout strategy is proposed, the problem of phoneme missing of the numeric string is solved, and the performance of a numeric string voice print identifying system is improved.
Owner:TIMESAFER BEIJING TECH
Obstacle detection method and device and storage medium
ActiveCN111598034AAvoid training of deep learning modelsImprove application deployment efficiencyScene recognitionElectromagnetic wave reradiationPhysicsData processing
The invention relates to an obstacle detection method and device and a storage medium, and belongs to the technical field of computers. The method comprises the steps: obtaining point cloud data collected by a laser detection module in a process that a moving carrier moves on a moving plane; wherein the point cloud data comprises three-dimensional coordinates of sampling points and reflection signal intensity; projecting the sampling points to a two-dimensional plane according to the three-dimensional coordinates by taking a height direction perpendicular to the moving plane as a projection direction to obtain a bird's-eye view; determining pixel information of each pixel point in the aerial view according to the point cloud data, wherein the pixel information of each pixel point comprisesa first pixel value, a second pixel value and a third pixel value; detecting obstacles in the collection range according to pixel information in the aerial view; the problem of low application deployment efficiency can be solved; by processing the point cloud data with huge data volume into the two-dimensional image data, a large amount of point cloud data does not need to be collected to train adeep learning model, and the application deployment efficiency is improved.
Owner:知行汽车科技(苏州)股份有限公司
Mobile context point cloud simplification algorithm based on point feature histogram
InactiveCN104732581AHigh streamlining rateRealize the function of adaptively setting the threshold3D modellingPoint cloudAlgorithm
The invention discloses a mobile context point cloud simplification algorithm based on a point feature histogram (namely a PFH operator). The algorithm mainly comprises the steps of receiving a point cloud set from a point cloud obtaining device; calculating the PFH operator of each point; calculating the standard deviation of the PFH of each point, and designing simplification rules; calculating out a corresponding relation table between the threshold values and the simplification rates of different standard deviations; according to the requirements to the simplification rate from a user, determining the threshold value; reserving the point sets with standard deviations less than or equal to the threshold value in point cloud data, in point cloud data, and eliminating other point sets. According to the mobile context point cloud simplification algorithm based on the point feature histogram, the simplification rate is high, the realtime performance is great, and adequate geometrical characteristics are reserved for scene reconstruction.
Owner:DONGHUA UNIV
MEMS driver circuit arrangement
InactiveUS6922499B2Avoid trainingFunction increaseSemiconductor/solid-state device detailsSolid-state devicesLow voltageHigh voltage
A packaged MEMS device containing the micro mirrors has mounted on it at least two distinct integrated circuit chips, at least one of which contains the low-voltage digital-to-analog converts and at least one of which contains the high-voltage amplifiers. The integrated circuit chips may be mounted directly to the MEMS package, or they may be indirectly mounted thereto, e.g., by being directly mounted to a multi-chip module which is in turn mounted on the package. Thus, the MEMS package is employed in a dual role, 1) that of package for the MEMS device and 2) the role of a backplane in that it contains mounting places and the wires interconnecting the MEMS device and chips or modules containing the low-voltage digital-to-analog converters and the high-voltage amplifiers.
Owner:LUCENT TECH INC +1
Federal learning method and system based on block chain and trusted execution environment
ActiveCN113837761AHigh Confidence VerificationPrevent model trainingMachine learningProtocol authorisationChain networkMachine learning
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Speedometer for train crossings
InactiveUS8054197B1Avoid trainingGood adhesionAudible signalsVisible signalsDisplay deviceEngineering
An apparatus that indicates the speed of oncoming trains at train crossings comprises a large digital display attached to a drop gate or alternately on a side gate crossing sign for those crossings without a gate. The digital display is surrounded by a large sign indicating the speed of an oncoming train. A speed detection device aimed in either direction on the track to determine train speed. An interface converts the detected speed into a digital display. It is envisioned that motorists knowing the speed of an oncoming train will be less likely to try to beat the train through the crossing.
Owner:MARTIN CHRIS +1
Logistics service prediction method and device, and readable storage medium
ActiveCN109214559AImprove forecasting efficiencyImprove predictive performanceForecastingMachine learningLogistics managementBusiness forecasting
A method and apparatus for predicting logistics services, a readable storage medium, the predicting apparatus for logistics services comprising: acquiring first historical data of logistics services;acquiring a shared parameter, the shared parameter being a shared parameter in a second prediction model corresponding to a second historical data of a logistics service, the second historical data ofthe logistics service being earlier than the first historical data of the logistics service; generating a first prediction model using a machine learning algorithm based on the first historical dataof the logistics service and the shared parameters, the first prediction model comprising: task parameters corresponding to the shared parameters and the first historical data of the logistics service; predicting a logistics service based on the first prediction model, and generating a prediction result. Applying the above scheme, the effect and efficiency of logistics business forecasting can betaken into account simultaneously.
Owner:ANJI AUTOMOTIVE LOGISTICS +1
Mobile Shredder
Owner:VECOPLAN
Lane changing decision-making method and device
ActiveCN109835339AThe determination process is simple and clearAvoid collectingSecure stateEngineering
The invention discloses a lane changing decision-making method and device; based on the obtained first motion information of a own vehicle and the second motion information of environment vehicles, the driving environment of the own vehicle is divided into different areas; the relative directions of the environmental vehicles and the own vehicle in each area are the same; a target vehicle in eacharea is determined; a lane changing flag bit of each area is in a safe state or an unsafe state is determined based on the a relative distance and a relative speed between the target vehicle in each area and the own vehicle; and a target lane changing decision is made according to the lane changing flag bit of each area. The driving environment of the own vehicle is divided into different areas; whether the target vehicle generating potential threats to normal driving of the own vehicle exists in all the areas or not is determined, such that the final target lane changing decision is made; thewhole lane changing decision making process is simple and clear, and collection and training of a large amount of data are avoided.
Owner:BEIJING JINGWEI HIRAIN TECH CO INC
Training system for training a generator neural network
ActiveUS20200364562A1Increase the number ofAccelerated trainingEnsemble learningCharacter and pattern recognitionData transformationEngineering
A training system for training a generator neural network arranged to transform measured sensor data into generated sensor data. The generator network is arranged to receive as input sensor data and a transformation goal selected from a plurality of transformation goals and is arranged to transform the sensor data according to the transformation goal.
Owner:ROBERT BOSCH GMBH
Plews impulse drive
InactiveUS20040035232A1Easy and efficient to manufactureImprove energy efficiencyGearingMachines/enginesCircular discLinear motion
An impulse drive for converting inertial and rotational energy into linear motion includes a pair of thrust mass bearing race, with one of the pair of thrust mass bearing race attached to the interior of the top circular bearing ring and another of the pair of thrust mass bearing race attached to the interior of the bottom circular bearing ring, an inner circular bearing ring is coupled to the pair of thrust bass bearing race and have movable arc segments that move into and away from the path of thrust mass that move radially freely within cavities of a rotating circular disk, the rotating circular disk is moved by a axle drive that varies the rotational velocity of the disk, a mass accelerator girdle is positioned exterior the inner circular bearing ring and coupled to the interior of the top and bottom circular bearing rings, with mass accelerators fastened into the mass accelerator girdle and positioned over pistons of the movable arc segments in such a fashion that the amount of force needed to accelerate the trust masses, and the resulting thrust generated by the device is contained and controlled.
Owner:PLEWS DENNIS J
Method and device for monitoring the satisfactory functioning of at least one first and a second component of a vehicle drive train
ActiveUS20130311034A1Satisfy functionCancellation effectVehicle testingHybrid vehiclesNormal functioningControl theory
The invention relates to a method for monitoring the proper functioning of at least one first and a second component (109, 110) of a vehicle drive train (100). The first and the second component (109, 110) each have an effect on the torque applied to the driveshaft (111) and are controlled for this purpose by a test signal (112, 113). The test signals (112, 113) are predetermined such that the effects of the first and the second component (109, 110) onto the torque applied to the driveshaft (111) cancel each other out if the first and the second component (109, 110) function properly. When the components (109, 110) function properly, the traveling comfort is not disturbed by an unexpected torque increase or torque decrease during the carrying out of this method. Any perturbation of the vehicle drive train (100) is therefore also avoided.
Owner:ROBERT BOSCH GMBH
Method for reinforcing soil body by combination of organic matter and plant urease
InactiveCN111827258AImprove mineral morphology and structureIncreased strength and effectBuilding constructionsOrganic fertilisersRice flourEnvironmental chemistry
The invention provides a method for reinforcing a soil body by a combination of organic matter and plant urease. The method includes the following steps of firstly, extracting the soybean urease; secondly, mixing the organic matter such as glutinous rice flour, brown sugar or skim milk powder into a solution of soybean urease in proportion; and thirdly, sequentially injecting the organic matter and urease mixed liquid and consolidating fluid into the soil body in certain proportion. According to the method, nucleation point locations are provided for calcium carbonate precipitation by introducing the organic matter into a urease induced calcium carbonate precipitation (EICP) technology so that calcium ions can be concentratedly adsorbed to anion groups provided by the organic mater and large-grained calcium carbonate crystals can aggregate at the nucleation point locations; the growth habit of mineral crystals is affected, the morphology structure of minerals is improved, and the strength of soil body is greatly improved and enhanced; and the activity of the urease is protected, and the calcium carbonate precipitation efficiency under a high concentration is slightly improved. Themethod is efficient, economical, simple in process, friendly to the environment, convenient to popularize and suitable for large-scale treatment.
Owner:HENAN UNIVERSITY
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