107 results about "Dual domain" patented technology

A computer chassis compliant with the Intelligent Platform Management Interface includes a central baseboard management controller (CBMC) and at least one computer board set. The computer board set includes a microcontroller that operates simultaneously as a satellite management controller to receive system management requests from the CBMC and to provide system management information to the CBMC, and as a local baseboard management controller to receive system management information about the computer board set and to provide the system management information about the computer board set to the computer board set. The computer board set detects a local event, which is entered in a local system event log. The satellite management controller determines if the event was requested by the CBMC, and if so, transmits a corresponding event message to the CBMC. The local baseboard management controller determines if local action is required and performs the local action.

A method for optically analyzing blood vessel walls comprises receiving optical signals from the vessel walls and resolving a spectrum of optical signals in wavelength to generate spectral data. The spectral data is then transformed into the frequency domain. In the preferred embodiment, this transformation is achieved by applying wavelet decomposition. In other embodiments other transform techniques such as Fourier analysis is applied. The spectral data in the frequency domain are then used to analyze the vessel walls. In the typical embodiment, the spectral data are used to analyze a disease state of blood vessels walls such as the presence of atherosclerotic plaques, and their state. Dual domain method enables the spectral signals from blood vessels to be analyzed simultaneously according to frequency and wavelength (time). Dual-Domain Regression Analysis (DRDA) and Dual-Domain Discrimination Analysis (DDDA) in combination with wavelet transform (WT) enable the modeling of signals simultaneously in both domains. This provides a mechanism for isolating the non-interesting variation in spectra, making the system and analysis method more robust against variations in instrument and environmental conditions, e.g., broad-band spectral variation contributed from water, heart motion, and other non-interesting interferences. This provides higher sensitivity and specificity when compared with other models currently being used.

This invention discloses one active digital image content identification method based on wavelet and DCT double areas, which comprises the following steps: send end processes water mark generation, imbedding and image identification and modification initial position, wherein, through above position to generate water mark images to restore property extraction and imbedding water mark and restoring.

A link simulation tool for simulating high-speed communications link systems is provided. Communications links may include link subsystems such as transmit (TX) circuitry, receive (TX) circuitry, oscillator circuits that provide reference clock signals to the TX and RX circuitry, and channels that link the TX and RX circuitry. The link simulation tool may model each of the subsystems using behavioral models. The behavioral models may include characteristic functions such as transfer functions, probability density functions, and eye characteristics. The link simulation tool may have a link analysis engine that is capable of performing two- dimensional (two-variable) convolution operations and in applying dual-domain (frequency-time) transformations on the characteristic functions provided by the behavioral models to simulate the performance of the link system.; The link simulation tool may have an input screen that allows a user to specify desired link parameters and a data display screen that display simulated results.

The invention discloses a dual-domain adaptive modular pyramid network. The network comprises an encoder, a pyramid type pooling module, a decoder, an image level domain adaptation module and a feature level domain adaptation module, the pyramid type pooling module is connected behind the encoder, the decoder is connected behind the pyramid type pooling module, and the encoder is connected with aconvolution layer with the same size as the decoder through a skip connection technology. According to the method, through adversarial training of images and feature levels, a target domain label is not needed during training, the test or use process works like a normal segmentation network, and an image level domain adaptation module and a feature level domain adaptation module are not needed; the method can improve the segmentation precision of the segmentation neural network in an unmarked new image, provides technical support for the recognition of streetscape and computer-aided diagnosisof robots and vehicles, is high in practicality, and is higher in popularization and application values.

The invention relates to a rapid magnetic resonance image reconstruction method based on undersampling, and the method comprises the following steps: step 1, collecting a large amount of magnetic resonance data, and taking the data as a data set of a deep reconstruction network model; step 2, performing data enhancement on the training data by using all mask matrixes possibly existing in the under-scanning process, and expanding the data set acquired in the step 1; step 3, performing normalization processing on the data set expanded in the step 2; step 4, establishing a double-domain parallel reconstruction network; and step 5, training the double-domain parallel reconstruction network established in the step 4 by using the data subjected to normalization processing in the step 3 to obtain a trained double-domain parallel reconstruction network, performing normalization preprocessing on an acquired pre-scanning image, sending the pre-scanning image into the trained network for forward propagation, and outputting the pre-scanning image to obtain a reconstructed image. According to the method, the network has the capability of performing high-definition reconstruction of the nuclear magnetic resonance image by using the undersampled data, and artifacts caused by the condition violating the sampling theorem can be eliminated.

The invention discloses a building edge point detection method based on double-domain graph signal filtering. The method comprises the following steps: collecting airborne laser radar data and generating three-dimensional point cloud data; based on the local feature statistical histogram and the elevation value of the vertex, constructing a double-domain signal graph of a spatial domain and a value domain; constructing a three-dimensional space weighted undirected signal graph model through a histogram cross kernel and a Gaussian function; carrying out edge perception smoothing on the signal graph model by utilizing bilateral filtering, and removing perigee and noise points; and based on the double-domain signal graph model, constructing a double-threshold high-pass filter to automaticallyextract building edge points. According to the invention, an airborne laser radar system and a POS system are used for collecting three-dimensional point cloud data of a surface building; and then athree-dimensional weighted double-domain signal graph is constructed based on a local feature statistical histogram, and bilateral filtering smoothing and double-threshold high-pass filtering edge detection is performed by using unused filters, thereby achieving the purpose of directly and accurately extracting building edge points from original point cloud data.

The invention discloses an I/Q domain modulation method, a dual-domain modulation method and a multiple access communication method depending on a spatial position, and belongs to the technical fieldof communication. According to the method, the dependence of physical layer safety communication on channel state information is eliminated, and the functions that a receiver at the expected positioncan normally communicate, and eavesdroppers at other positions cannot receive signals or can only receive error signals are achieved. The security capability of the wireless communication system is improved in space dimension. According to the multiple access communication method provided by the invention, multiple users can be distinguished according to the spatial accurate position points. Evenif a plurality of users are located in the same angle domain sector, as long as the spatial positions of the users are different, the method provided by the invention can be used for carrying out multiple access communication, so that the spatial reuse rate of the system is further improved, and the capacity of the system is improved.

The invention provides an array substrate, a driving method, a liquid crystal display panel and a display device, and aims to solve the problem that the display brightness of pixel is not the same under a same gray level. The array substrate provided by the invention comprises a public electrode group and pixel electrodes, wherein the public electrode group and the pixel electrodes are arranged on different layers; the pixel electrodes are pixel electrodes of a dual-domain structure at least; the public electrode group comprises public electrodes of a plurality of areas which are not connected; adjacent same-domain pixel electrodes with the highest display brightness at a same gray level correspond to public electrodes in a same area, of the public electrode group; public electrodes with the highest display brightness in different areas, at a same gray level, are loaded with constant voltage signals; public electrodes in other areas, of the public electrode group, are loaded with complex voltage signals which adopt the constant voltage signals as reference and have preset vibration amplitudes.

The invention relates to a neural network magnetic resonance image reconstruction method based on double-domain alternating convolution. The neural network magnetic resonance image reconstruction method is characterized by comprising the following steps: the step 1, obtaining a K space data set; the step 2, generating under-sampling K space data; the step 3, establishing a coding and decoding neural network structure of double-domain alternating convolution; the step 4, training a coding and decoding neural network model of double-domain alternating convolution by using the under-sampled K space data generated in the step 2 and image domain data obtained by performing inverse Fourier transform on the K domain information in the step 1; and the step 5, reconstructing the undersampled magnetic resonance data by using the trained double-domain alternating coding and decoding neural network to obtain a magnetic resonance reconstructed image with relatively high definition. According to the method, accelerated reconstruction of magnetic resonance imaging is realized by using the small kernel convolutional neural network on the K domain, artifacts caused by breaking through the Nyquist sampling limit are eliminated, meanwhile, clear magnetic resonance imaging can be reconstructed, and the reconstruction precision is improved.

The invention discloses a display panel and a display device, and relates to the technical field of display. The display panel comprises a first substrate and a second substrate which are oppositely arranged, a plurality of sub-pixel regions and first electrodes located inside the sub-pixel regions. The first electrodes include first sub-electrodes, second sub-electrodes and third sub-electrodes.The sub-pixel regions include a first domain region, a domain boundary region and a second domain region which are sequentially arranged in the second direction, the width of the domain boundary region is A, a black matrix comprises a first black matrix, the orthographic projection of the first black matrix in the plane where the first substrate is located and the domain boundary region are overlapped, the width of the first black matrix is B, B is larger than or equal to B1 and smaller than or equal to B2, B1 is equal to -1.48+0.95A, and B2=-3.04+1.28A. According to the scheme, the contrast ratio of the display panel and the display device is increased, and the display performance of the display panel and the display device of the dual-domain structure is improved.

The invention provides a cross-domain semantic segmentation method based on graph convolution and contrast learning, and belongs to the field of transfer learning and computer vision. The invention designs a method for solving an adjacent matrix in different domains, and provides a new thought for establishing a long-distance context relationship between the domains. In order to solve the problem of unbalanced distribution of different categories, learning loss is grouped and compared. Secondly, in order to extract domain-invariant information, a newly proposed double-domain adjacent matrix is utilized to perform graph convolution operation; in the process of graph convolution operation, a graph structure is constructed on a feature graph, and in order to establish a long-distance context relationship between domains, the graph convolution operation is creatively completed in the proposed graph structure by using the proposed double-domain adjacent matrix. According to the method provided by the invention, a long-distance context relationship between domains is established, domain-invariant information can be extracted more effectively, and a better evaluation result is obtained in subjective and objective evaluation.

The invention discloses an image super-resolution method based on a hierarchical residual neural network. A hierarchical residual learning strategy and a double-domain enhancement module are adopted to construct a hierarchical residual neural network model, the hierarchical residual neural network model is used for learning a complex mapping relationship between a low-resolution image and a high-resolution image, and then the trained network model is utilized to reconstruct the high-resolution image from the input low-resolution image, wherein the hierarchical residual neural network model iscomposed of a feature extraction layer, a feature mapping layer and a feature fusion layer, the feature extraction layer is composed of a convolution module, the feature mapping layer is composed of aplurality of double-domain enhancement modules in a cascaded mode, and the feature fusion layer is composed of an up-sampling module and a convolution module. According to the method, a better high-resolution image can be reconstructed, and the method has the advantages of being small in network model parameter quantity and high in calculation efficiency.

The present invention relates to a nanocomposite ocular device that can release drugs within a close distance to the ocular surface and provide controlled and sustained release of the drug at a constant rate. The device can achieve both optical and medical functions. The device comprises a drug, one or more reservoir domains, and a barrier layer configured to block the drug diffusion paths from the reservoir domain to the ocular surface in the eye of the subject, wherein the drug partitions between the reservoir domain and the barrier layer, and the equilibrium drug solubility in the reservoir domain is at least five folds higher than that in the barrier layer.

The invention discloses an image synthesis method based on a convolution neural network, comprising the following steps: Step 1: Pre-processing the 3T-7T training image pair and the test 3T magnetic resonance image to obtain the pre-processed 3T-7T training image pair and the pre-tested 3T magnetic resonance image; Step 2 Constructing a dual-domain convolutional neural network model, inputting thepre-processed 3T-7T training image the dual-domain convolutional neural network model for training, and obtaining the trained dual-domain convolutional neural network model; Step 3, using processed test 3T magnetic resonance image as the current 3T magnetic resonance image, and inputing the current image into the trained dual domain convolutional neural network model to obtain a 7T magnetic resonance image corresponding to the current 3T magnetic resonance image.

The invention discloses a novel pulse node type scalar point multiplication double-domain implementation system and method, which adopts a semi-autonomous learning design combining random dynamic table establishment and coordinate mapping derivation formula calculation, combines and uses pulse node values and high-frequency node values in the random table establishment, and adopts the advantage of integration of storage and calculation in the derivation formula, so as to realize the double-domain implementation of the pulse node type scalar point multiplication. The node calculation value position is the position in the random table, so that the cross calling of the formula mapping calculation value and the point value data in the random table is realized, finally, the efficient operation of the pulsation node with the memory of the scalar point multiplication data is realized, and the overall implementation efficiency of the scalar point multiplication is improved; the method is mainly applied to the function implementation of the cryptographic service of the asymmetric cryptography based on the elliptic curve, and the scalar point multiplication operation on the Fp domain and the scalar point multiplication operation on the Fp2 domain are emphatically realized, so that the application of encryption and decryption and signature verification of SM2 and SM9 algorithms is supported.

The invention discloses a method for constructing a ROM-based dual-domain mobile phone system. The dual-domain mobile phone system comprises a master domain based on a mobile phone kernel, a slave domain and a domain management program. The method specifically comprises the following steps: step 1: adding a code supporting a dual-domain function to the original mobile phone kernel, and compiling and generating a new kernel binary file; step 2: modifying a boot. img mapping file of the master domain; step 3: modifying system. img mapping files of the master domain and the slave domain; and step4: respectively burning the boot. img mapping file of the master domain, the system. img mapping file of the master domain and the system. img mapping file of the slave domain in corresponding flashsubareas of a mobile phone. Therefore, by adoption of the method disclosed by the invention, the coupling degree between a dual-domain system and a mobile phone manufacturer can be reduced, and moreover a third party mobile phone security solution provider can develop and apply an own dual-domain system while the own benefits of the mobile phone manufacturer is protected.

The invention provides an image denoising method, system and device and a storage medium, and the method comprises the steps: constructing an image denoising model which is used for carrying out the feature mapping of a wavelet domain and the feature mapping of a spatial domain on an input image with noise, and obtaining a denoised image; training the image denoising model; and inputting a to-be-processed image into the trained image denoising model to obtain a denoised image output by the image denoising model. The invention provides a novel image denoising model based on a double-domain network, feature extraction and mutual complementation are carried out on a spatial domain and a wavelet domain at the same time, image noise can be effectively removed, the signal-to-noise ratio of the image is improved, detail information such as textures and edges of the image can be recovered, and therefore a more ideal image denoising effect is obtained.