2751 results about "Spatial structure" patented technology

A combined-rib cavity member for space-structure flooring includes cavity form and structure bottom plate, which are connected into one integral whole. It is characterized by that there are at least two cavity forms arranged alternate with each other on the structure bottom plate, its side forms with the structure bottle plate at least one subrit form cavity of casti-in-situ structure, and other other sides of the cavity form forms the side fromboard of main rib or beam or wall for cast-in-situ structure. By this, the subrib of cast-in-situ structure can be formed in the sub-rib form cavity on the structure battom plate, the sub-rib participates in load bearing of structural bottom slat, cast-in-situ main rib, cast-in-sita upper slab so to a load-bearing space structure, improved mechanical property, raise integrity and anti-shock property, decrease structural wt. lower cost and make construction be convenient.

A method for stimulating a particular area of a brain using a stimulation device includes detecting a spatial structure of a head and determining electrical and/or magnetic properties of at least one part of anatomical structures of the head. An energy amount to be provided by the stimulation device for stimulating the particular area of the brain is calculated automatically based on the spatial structure of the head and the determined electrical and/or magnetic properties of at least one part of the anatomical structures of the head.

The invention relates to a method for stimulating specific areas of a brain using an induction device, comprising the following steps: recording the spatial structure of the head, in particular the brain; generating a simulation model of the induction device; and arranging the induction device relative to the head such that a specific area of the brain determined by means of the simulation model of the induction device is stimulated by a current flowing in the induction device, as well as to a method for stimulating specific areas of a brain using an induction device, comprising the following steps: recording the spatial structure of the head, in particular the brain; generating a simulation model of the head; and arranging the induction device relative to the head such that a specific area of the brain determined by means of the simulation model of the head is stimulated by a current flowing in the induction device, as well as to a device for stimulating specific areas of a brain using an induction device connected to a marker.

The invention relates to a precast hollow floor board with spatial structure and its application. The floor board includes hollow form and cavity, and features including structural bottom slab and structural sub-rib. The structural bottom slab and structural sub ribs contain reinforcing bars or wire mesh to form an integrated load-bearing member with an inverted T-shape. There are exposed bars ormesh on the structural bottom slab. The thicknesses of structure bottom slab and structural sub-rib are larger than the thickness of hollow form whose upper part and side parts are connected to the structural sub-rib, and lower part is connected to the structural bottom slab so as to form a closed integral body. The invented precast hollow floor board possesses advantages of simple structure, high strength, easy for handlings, good shock resistance and reduced structural dead wt..

A method and an apparatus for noninvasively and quantitatively determining spatially resolved absorption and reduced scattering coefficients over a wide field-of-view of a food object, including fruit or produce, uses spatial-frequency-domain imaging (SFDI). A single modulated imaging platform is employed. It includes a broadband light source, a digital micromirror optically coupled to the light source to control a modulated light pattern directed onto the food object at a plurality of selected spatial frequencies, a multispectral camera for taking a spectral image of a reflected modulated light pattern from the food object, a spectrally variable filter optically coupled between the food object and the multispectral camera to select a discrete number of wavelengths for image capture, and a computer coupled to the digital micromirror, camera and variable filter to enable acquisition of the reflected modulated light pattern at the selected spatial frequencies.

The disclosed terrain model is a generative, probabilistic approach to modeling terrain that exploits the 3D spatial structure inherent in outdoor domains and an array of noisy but abundant sensor data to simultaneously estimate ground height, vegetation height and classify obstacles and other areas of interest, even in dense non-penetrable vegetation. Joint inference of ground height, class height and class identity over the whole model results in more accurate estimation of each quantity. Vertical spatial constraints are imposed on voxels within a column via a hidden semi-Markov model. Horizontal spatial constraints are enforced on neighboring columns of voxels via two interacting Markov random fields and a latent variable. Because of the rules governing abstracts, this abstract should not be used to construe the claims.

The invention discloses a video content description method by means of space and time attention models. The global time structure in the video is captured by means of the time attention model, the space structure on each frame of picture is captured by the space attention model, and the method aims to realize that the video description model masters the main event in the video and enhances the identification capability of the local information. The method includes preprocessing the video format; establishing the time and space attention models; and training and testing the video description model. By means of the time attention model, the main time structure in the video can be maintained, and by means of the space attention model, some key areas in each frame of picture are focused in each frame of picture, so that the generated video description can capture some key buy easy neglected detailed information while mastering the main event in the video content.

The invention discloses a large-scale building information model and a three-dimensional digital city integration method, and belongs to the field of spatial information technology. Interactive construction is carried out on the building information model on the basis of construction drawings, then the building information model is converted into a building component information model through spatial and semantic information mapping, a building component information base is established, and integrated application of building component information is carried out in three-dimensional digital city scenes. A large-scale indoor spatial structure data source is provided for a three-dimensional digital city, and the utilization rate of data is improved; internal spatial structures of buildings and external environments are displayed integrally. The building component information model with consistent semantic and spatial information is established, various sensors in the buildings can be integrated, and useful supports are provided for smart city application.

An exemplary methodology, procedure, system, method and computer-accessible medium can be provided for receiving physiological data for the subject, extracting one or more patterns of features from the physiological data, and classifying the at least one state of the subject using a spatial structure and a temporal structure of the one or more patterns of features, wherein at least one of the at least one state is an ictal state.

Extracting features from signals for use in classification, retrieval, or identification of data represented by those signals uses a “Distortion Discriminant Analysis” (DDA) of a set of training signals to define parameters of a signal feature extractor. The signal feature extractor takes signals having one or more dimensions with a temporal or spatial structure, applies an oriented principal component analysis (OPCA) to limited regions of the signal, aggregates the output of multiple OPCAs that are spatially or temporally adjacent, and applies OPCA to the aggregate. The steps of aggregating adjacent OPCA outputs and applying OPCA to the aggregated values are performed one or more times for extracting low-dimensional noise-robust features from signals, including audio signals, images, video data, or any other time or frequency domain signal. Such extracted features are useful for many tasks, including automatic authentication or identification of particular signals, or particular elements within such signals.

A 2D or 3D velocity field is reconstructed from a cross-correlation analysis of image pairs of a sample, without first reconstructing images of the sample spatial structure. The method can be implemented via computer tomographic x-ray particle image velocimetry, using multiple projection angles, with phase contrast images forming dynamic speckle patterns. Estimated cross-correlations may be generated via convolution of a measured autocorrelation function with a velocity probability density function, and the velocity coefficients iteratively optimised to minimise the error between the estimated cross-correlations and the measured cross-correlations. The method may be applied to measure blood flow, and the motion of tissue and organs such as heart and lungs.

The invention provides a high-speed detection system and method of tunnel defects. The system comprises a master control unit, a linear laser, an area array charge coupled device (CCD) camera, an image compression unit, a displacement sensor, a synchronous controller, an image storage unit, a storage module, a correction module and an inertial navigator. A special measurement locomotive serves as a mobile monitoring platform for the design and is particularly suitable for subway tunnel monitoring, and subway and other tunnel space structures can be effectively, rapidly and dynamically measured; the actually measured data is compared with actual real distance, errors are analyzed, the parameter setting is adjusted, and the measurement accuracy is greatly improved; moreover, the XYZ axial vibration of the mobile monitoring platform is subjected to error correction through the inertial navigator, and a measurement error is prevented from being introduced into mobile measurement.

The method of complicated tubular netted tissue engineering rack forming technology based on core dissolving technique belongs to the field of tissue engineering rack manufacturing technology. The technological process includes first designing 3D model of rack and rack core; making rack core with water soluble material without biotoxicity through fast laminated formation; compounding solution of biocompatible material with proper amount of pore creating agent and coating the solution onto the rack core; air drying, soaking in distilled water to dissolve out rack core and pore creating agent, taking out and volatilizing water and coating different forming material with or without pore creating agent successively to form the tubular netted rack with complicated spatial structure, different material gradient and different pore gradient.

The invention discloses a target space knowledge and two-stage prediction learning-based target detection method. By utilizing various data conversion methods, a sample number is increased and samplediversity is improved; two deep neural networks including SSD and newly designed RefineNet are trained; for a prediction target with a relatively high probability in a primary prediction result of theSSD, the accuracy of judgment is further improved through the RefineNet; and by establishing peculiar spatial structure constraint rules of the target, the wrong prediction is reduced, thereby obtaining a final detection result. Compared with a few existing methods, the method provided by the invention has the advantages that visual and spatial characteristics of a remote sensing target are considered at the same time; and end-to-end target candidate selection, feature extraction and classified locating are realized by utilizing the deep networks with excellent feature extraction capabilities, so that the detection rate of the remote sensing target is remarkably increased and the false alarm rate is reduced.

The present application relates to a method and a device for parsing a table in a document image. The method comprises the following steps: inputting a document image to be parsed which includes one or more table areas into the electronic device; detecting, by the electronic device, a table area in the document image by using a pre-trained table detection model; detecting, by the electronic device, internal text blocks included in the table area by using a pre-trained text detection model; determining, by the electronic device, a space structure of the table; and performing text recognition on a text block in each cell according to the space structure of the table, so as to obtain editable structured data by parsing. The method and the device of the present application can be applied to various tables such as line-including tables or line-excluding tables or black-and-white tables.

The invention belongs to the technical fields of mode indentifying and image processing, and relates to an image matching method based on characteristic points. The image matching method based on characteristic points defines an annular corner code model according to the K neighboring structure of the characteristic points and applies the model to point mode matching. Similar annular corner codes not only describe the similarity of the space structures of two characteristic points, but also can be used for local mapping estimation. The similarity of the two characteristic points is confirmed by the similar length of the largest similar annular corner codes associated with the two characteristic points. The image matching method based on characteristic points carries out structure matching according to the similarity of the local space structures of the characteristic points, and uses the local mapping and clustering to carry out optimization matching. The optimization matching result is used for optimizing the mapping estimation. The method can be used for the image matching based on the characteristic points, image jointing and embedding, motion tracing, information fusion of medical single-mode and multi-mode images, as well as image searching based on contents.

The invention belongs to the fiber sensing technical field, and specifically relates to a multi-core fiber bragg grating (FBG) universal bending sensor; the multi-core fiber bragg grating (FBG) universal bending sensor is suitable for smart material and structure on-line detection and analysis, can control and monitor space structure space three dimensional positions and attitudes, and is formed by using the multi-core fiber bragg grating (FBG) as the basic sensing unit; the multi-core fiber bragg grating (FBG) universal bending sensor comprises multi-core fibers including one center fiber core, and the resting fiber cores are arranged around the center fiber core in quadrature distribution or symmetrical distribution; each fiber core in the same transverse position of the multi-core fiber uses the same phase mask slice to simultaneously expose the FBG; the central wavelengths of various Bragg gratings on the multi-core fiber are different; the multi-core fiber bragg grating (FBG) universal bending sensor can monitor various reflection wavelength changes of the multi-core FBG, thus measuring the bending amplitude and direction angles.

The invention discloses a non-linear structure light illumination microscopic imaging method which comprises the following steps: 1) loading a computed hologram on a digital microscopic array; 2) generating a first spatial structure light field which meets sine distribution and is used for activating fluorescent protein, and radiating the first spatial structure light field to the surface of a sample, so as to convert a part of protein to be in an illuminated state from a dark state; 3) radiating the sample in a second spatial structure light field so as to enable fluorescent protein in the bright state to emit fluorescent light, collecting the fluorescent light, and imaging in a photoelectric detector; 4) repeating the step 2) and the step 3), acquiring a plurality of spatial frequencies, acquiring a plurality of initial phases in each direction to obtain a plurality of original images, and reestablishing a super-resolution image according to a GPU acceleration algorithm. The invention further discloses a non-linear structure light illumination microscopic imaging system. The non-linear structure light illumination microscopic imaging method has the advantages of relatively high system imaging resolution, high fluorescent drifting resistance, low phototoxicity and rapid imaging.