364 results about "Middle level" patented technology

The present invention provides control methods, control systems, and control software for microfluidic devices that operate by moving discrete micro-droplets through a sequence of determined configurations. Such microfluidic devices are preferably constructed in a hierarchical and modular fashion which is reflected in the preferred structure of the provided methods and systems. In particular, the methods are structured into low-level device component control functions, middle-level actuator control functions, and high-level micro-droplet control functions. Advantageously, a microfluidic device may thereby be instructed to perform an intended reaction or analysis by invoking micro-droplet control function that perform intuitive tasks like measuring, mixing, heating, and so forth. The systems are preferably programmable and capable of accommodating microfluidic devices controlled by low voltages and constructed in standardized configurations. Advantageously, a single control system can thereby control numerous different reactions in numerous different microfluidic devices simply by loading different easily understood micro-droplet programs.

A programming-device user interface may include multiple levels of abstraction for programming treatment settings. A stimulation zone-programming interface may be at a highest level of abstraction and may include idealized stimulation zones. A field strength-programming interface may be at a middle level of abstraction and may include electromagnetic field-strength patterns generated by the stimulation zones, and / or electrode settings, and a depiction of how the electromagnetic fields interact with each other. An electrode-programming interface may be at a lowest level of abstraction and may depict treatment settings at an electrodes-view level. These interfaces may include a display of a stimulatable area of the patient's body. The display may include a depiction of leads and / or the underlying physiology, such as a depiction of a portion of a spine. Algorithms map treatment settings from one level of abstraction to settings at one or more other levels of abstraction.

The invention relates to multilayer honey-net data transmission method and system, and the gateway of honey-net receives the data flow of external network; the gateway of honey-net detects the network intrusion for the received data flow; the normal data flow can pass, which is sent to the target host computer; and the informal data flow is divide into high, middle and low according to dangerous level; and the data flow with high level is sent to physical honey-tank system, the data flow with middle level is sent to virtual machine honey-tank system, and the data floe with low level is sent to virtual honey-tank system. The invention can utilize the advantages of low interactive honey-tank system and high interactive honey-tank system, save system source, and improve the covering area of honey-tank system and the ability of obtaining the movable information of network attack and capturing the malice code; it can defeat the anti-honey tank technique. And it can be used in security field of computer network.

The present invention provides control methods, control systems, and control software for microfluidic devices that operate by moving discrete micro-droplets through a sequence of determined configurations. Such microfluidic devices are preferably constructed in a hierarchical and modular fashion which is reflected in the preferred structure of the provided methods and systems. In particular, the methods are structured into low-level device component control functions, middle-level actuator control functions, and high-level micro-droplet control functions. Advantageously, a microfluidic device may thereby be instructed to perform an intended reaction or analysis by invoking micro-droplet control function that perform intuitive tasks like measuring, mixing, heating, and so forth. The systems are preferably programmable and capable of accommodating microfluidic devices controlled by low voltages and constructed in standardized configurations. Advantageously, a single control system can thereby control numerous different reactions in numerous different microfluidic devices simply by loading different easily understood micro-droplet programs.

[Problem] An underpants type disposable diaper cover capable of firmly holding an absorbent pad.[Means for Solving Problems] In an underpants type disposable diaper cover comprising a front body part (F) and a back body part (B) which are formed in such a manner as to be continuous with each other at a crotch portion and both side portions, thereby creating a waist opening (23) and a pair of right and left leg openings, and an absorbent pad (10) which is detachably attached to an inner surface thereof, a plurality of waist portion-elastic members (24) are spaced, reaching from one side to the other side, in a longitudinal direction along the waist opening (23) in the front and back body parts (F, B), a plurality of curved elastic members (26, 28) are spaced without intersecting each other in each of the front and back body parts (F, B), which extend from an upper level with respect to a middle level in a longitudinal direction on one side in a lateral direction, to an upper level with respect to a middle level in the longitudinal direction on the other side in the lateral direction, and extend so as to be curved toward the crotch portion with increasing closeness to a central portion in the lateral direction; and a curved portion of at least one of the curved elastic members (28) is configured in the front body part (F) as to pass on both sides with respect to an upper end portion of the attached absorbent pad.

The present invention discloses a 3-layer Virtual Private Network (VPN) which comprises P devices and PE devices in the backbone network, a plurality of sites and CE devices in subscribers' VPNs, and Hierarchy of PE (HoPE) devices, said HoPE devices serve as edge routers in the backbone network and are connected to P devices in the backbone network as well as sites and CE devices in subscribers' VPNs; said HoPE devices comprise understratum PEs (UPEs), zero or more middle-level PEs (MPES) and superior PEs (SPEs) connected with each other, and all of said PEs (UPEs, MPEs, and SPEs) take different roles and deliver the function of a central PE. For the SPEs, the routing and forwarding performance should be relatively higher; while for UPEs, the performance may be lower. The architecture according to the present invention can enhance the expandability in hierarchical BGP / MPLS VPNs.

The invention discloses a block chain system for implementing a hotspot account. The block chain system is divided into a plurality of levels from top to bottom, and specifically includes: a top-level block chain network node located at the top level in the plurality of levels, a middle-level block chain network node at the middle level in the plurality of levels, and a plurality of bottom-level chain block network nodes at the bottom level in the plurality of levels. The number of levels in the top level and the number of levels in the bottom level are respectively one. The number of levels in the middle level is N, and N is an integer greater than or equal to 0. A hotspot account at least comprises: a plurality of bottom-level sub-accounts respectively disposed in the different bottom-level block chain network nodes and at least one upper-level account disposed in the top-level block chain network node and / or the middle-level block chain network node, wherein, each upper-level account and each bottom-level sub-account have the same account ID and management secret key and are used for parallel processing of each Internet transaction related to the hot-point account.

The present invention proposes a dynamically reconfigurable multistage parallel single instruction multiple data array processing system which has a pixel level parallel image processing element array and a row processor array parallel. The PE array mainly implements a linear operation which is adapted to be executed in parallel in the low and middle levels of image processing and the RP array implements an operation which is adapted to be executed in row-parallel in the low and middle levels of image processing or more complex nonlinear operations. In particularly, such a system may dynamically reconfigure a SOM neural network in a low cost of performance and area, and the neural network supports high level of image processing such as a high speed online neural network training and image feature recognition, and completely overcomes a defect in which a high level of image processing can't be done by pixel-level parallel processing array in the existing programmable vision chip and parallel vision processor, and facilitate an intelligent and portable real time on-chip vision image system with a complete function at low device cost and low power consumption.

The invention discloses a deep learning saliency detection method based on the global a priori and local context. The method includes the steps of firstly, performing superpixel segmentation for a color image and a depth image, obtaining a global a priori feature map of each superpixel based on middle-level features such as compactness, uniqueness and background of each superpixel, and further obtaining a global a priori saliency map through a deep learning model; then, combining the global a priori saliency map and the local context information in the color image and the depth image, and obtaining an initial saliency map through the deep learning model; and finally, optimizing the initial saliency map based on spatial consistency and appearance similarity to obtain a final saliency map. The method of the invention can be used for solving the problem that a traditional saliency detection method cannot effectively detect a salient object in a complex background image and also for solving the problem that a conventional saliency detection method based on deep learning leads to false detection due to the presence of noise in the extracted high-level features.

A method detects roads in an aerial image of ground topology by determining low-level features, such as intensities and gradients, for each pixel in the aerial image, determining middle-level features, such as an orientation for each pixel from the low-level features, and determining high-level features from the middle-level features. Each high-level feature is assigned a probability, and the probabilities of the high-level features for each pixel are normalized and aggregated to a single probability that the pixel is associated with a road.

A programming-device user interface may include multiple levels of abstraction for programming treatment settings. A stimulation zone-programming interface may be at a highest level of abstraction and may include idealized stimulation zones. A field strength-programming interface may be at a middle level of abstraction and may include electromagnetic field-strength patterns generated by the stimulation zones, and / or electrode settings, and a depiction of how the electromagnetic fields interact with each other. An electrode-programming interface may be at a lowest level of abstraction and may depict treatment settings at an electrodes-view level. These interfaces may include a display of a stimulatable area of the patient's body. The display may include a depiction of leads and / or the underlying physiology, such as a depiction of a portion of a spine. Algorithms map treatment settings from one level of abstraction to settings at one or more other levels of abstraction.

The invention relates to an RGB-D image classification method and system. The method comprises the steps of: S1, utilizing a convolution neural network (CNN) to process a source RGB image and a Depth image respectively, and extracting low level characteristics; S2, utilizing a recursion neural network (RNN) to carry out feedback learning on the image low level characteristics, and extracting image middle level characteristics; S3, adopting a block interior constraint dictionary learning method, carrying out characteristic set sparse expression on the image middle level characteristics, and obtaining high level characteristics of the RGB-D images; and S4, inputting the high level characteristics of the RGB-D images into a linear SVM to complete the classified identification of the RGB-D images. According to the invention, automatic characteristic extraction of the images is realized, learning RGB-D image characteristic expressions can effectively distinguish classification of noise data from high similarity images, and the classification precision of the RGB-D images is improved; in addition, the linear SVM is utilized, and the image classification speed is improved.

The invention discloses an MMC (modular multiple converter) type multi-port power electronic transformer applied to an alternating current / direct current hybrid power distribution network. The multi-port power electronic transformer comprises an input level, a middle level and an output level, and are equipped with four kinds of universal interfaces: a high-voltage alternating current interface, a high-voltage direct current interface, a low-voltage alternating current interface and a low-voltage direct current interface; the input level refers to the MMC; the middle level refers to an isolating dual active full-bridge DC / DC converter; and the output level refers to a three-phase four-wire-system full-bridge inverter. Except the basic functions of voltage transformation, isolation, energy transfer and the like as a common transformer, the transformer provided by the invention can realize access of voltages of various forms with the multiple working modes, can perform functions of power flow control, electric quality adjustment and the like; and therefore, an intelligent power distribution network interface with higher applicability is configured.

A bank for defining the regions in which pixels are formed has a stacked structure including: a base layer on the low level which also serves as an interlayer insulating film between the pixel forming regions; a middle bank layer on the middle level which serves to improve the fixation of an organic compound material (i.e., improve the uniformity of the film thickness of a positive hole transporting layer and an electron-transporting light emitting layer) in forming an organic EL layer; and a bank metal layer on the upper level which is made of a conductive material and serves also as a common voltage line (cathode line).

The invention provides a method, device and terminal for determining an identity identification of a human face in a human face image. The method includes the step of obtaining an original characteristic vector of the human face image, selecting k candidate vectors from a human face image database according to the original characteristic vector, choosing a matching vector of the original characteristic vector from the k candidate vectors, and determining an identity identification, recorded in the human face image database, of the matching vector as the identity identification of the human face in the human face image according to the matching vector of the original characteristic vector. According to the method, device and terminal, low-lever human face characteristic vectors and middle-level characteristic vectors formed by interacting with self-correlation and mutual-correlation submatrixes in a combined Bayesian probability matrix are stored in the human face image database, the middle-level characteristic vectors contain characteristic vectors of human faces and information interacting with the self-correlation and mutual-correlation submatrixes in the combined Bayesian probability matrix, and efficiency and accuracy of human face identification can be improved.

The present invention discloses a method for pedestrian weight recognition in a video surveillance scene. The method is implemented through the following steps: S1, pre-training an FT-FNN network; S2, fine-tuning the FT-FNN network; S3, extracting a depth feature and an attribute feature of a training image; S4, optimizing the attribute weight; S5, extracting the attribute feature of a to-be-recognized image; S6, extracting the attribute feature of a pedestrian bank; S7, generating a distance matrix; and S8, outputting matching images in sequence. The depth feature after fine-tuning has strong distinguishing ability for the pedestrian weight recognition; compared with the texture, color and other low-level visual features, the middle-level semantic attributes are stable and not easy to change greatly with the change of the light and the posture; and manual integration of low-level vision features can improve the distinguishing ability of the depth feature to a certain extent, and can improve accuracy of some middle-level attributes closely related to the color and the texture, so that by combining the three advantages, the method disclosed by the present invention achieves better accuracy in the field of pedestrian weight recognition.

The invention discloses an RGB-D salient object detection method based on foreground and background optimization. The method comprises the following steps: initial foreground modeling is performed based on low-level feature contrast, and a superpixel-level initial salient figure is obtained; a middle-level aggregation processing is performed on the superpixel-level initial salient figure, and a middle-level salient figure is obtained; a high-level prior is introduced in the middle-level salient figure to improve the detection effect, and a foreground probability is generated; edge connectivity mixing depth information is calculated, and the edge connectivity is converted into a background probability; the foreground probability and the background probability are optimized, and a objective function is obtained; the objective function is solved, a optimal salient figure is obtained, and the detection of a salient object is realized. According to the invention, a optimization framework based on foreground and background measurement and the depth information of a scene is fully utilized by the invention, a high recall rate can be obtained, and the accuracy is high; the method can accurately position the salient object in different scenes and different sizes of objects and can also obtain nearly equal salience values in the target object.

A receptacle connector includes an insulative housing defining a base and a mating tongue extending from the base with a widen and thicken step structure formed around a root of the mating tongue near to the base, two rows of plate contacts disposed in the insulative housing with contacting sections exposed upon the mating tongue and in front of the step structure and categorized with signal contacts, power contacts and grounding contacts, and a metallic shielding plate disposed within a middle level of the mating tongue and occupying most portions of said mating tongue. The shielding plate defines a pair of immoveable and un-deflectable lateral edge sections in front of the step structure, each lateral edge section is configured to be adapted to be locked with a latch of a plug connector in a transverse direction.

The invention relates to a method for detecting a region of interest, called ROI for short, from bottom to top based on combination of low-level image information and middle-level image information. The method for detecting the region of interest comprises the steps that firstly, an angular point is detected through the Harris operator, so that a convex hull boundary is obtained, and a middle-level information saliency map is calculated according to a convex hull area and a superpixel clustering result; secondly, an image which is originally in the RGB space is converted into the CIELab space, and filtering is conducted on the image through a Gaussian difference filter, so that a low-level information saliency map is obtained; finally, weight fusion is conducted on the low-level image information and the middle-level image information so that a saliency map of the image can be obtained. According to the method for detecting the region of interest, through the combination of the middle-level image information calculated through superpixel clustering and the low-level image information calculated through filtration of the difference filter, accurate positioning of the region of interest in the complicated natural environment is achieved, and the edge of a detected object of interest is clear; meanwhile, background noise can be effectively restrained, and the applicability is high.

A pillar reinforcement of a center pillar comprises an upper part and a lower part with a boundary line of these parts being positioned below the middle level of the pillar reinforcement. The upper and lower parts respectively include side wall portions which extend along a vehicle side face and pairs of vertical wall portions which extend inwardly from front and rear end portions of the side wall portions. The pair of vertical wall portions of the lower part is slant relative to the vehicle width direction so that the distance between the vertical wall portions becomes wider toward the inward direction, and a slant angle of the pair of vertical wall portions of the lower part is greater than that of the vertical portions of the upper part.

An FPGA architecture has top, middle and low levels. The top level of the architecture is an array of the B16x16 tiles arranged in a rectangular array and enclosed by I / O blocks on the periphery. On each of the four sides of a B16x16 tile, and also associated with each of the I / O blocks is a freeway routing channel. A B16x16 tile in the middle level of hierarchy is a sixteen by sixteen array of B1 blocks. The routing resources in the middle level of hierarchy are expressway routing channels M1, M2, and M3 including groups of interconnect conductors. At the lowest level of the semi-hierarchical FPGA architecture, there are block connect (BC) routing channels, local mesh (LM) routing channels, and direct connect (DC) interconnect conductors. Each BC routing channel is coupled to an expressway tab to provide access for each B1 block to the expressway routing channels M1, M2, and M3, respectively. Each BC routing channel has nine interconnect conductors which are grouped into three groups of three interconnect conductors. Each group of three interconnect conductors is connected to a first side of a Extension Block (EB) 3x3 switch matrix. A second side of each EB 3x3 switch matrix is coupled to the E-tab. Between adjacent B1 blocks, in both the horizontal and vertical directions, the leads on the second side of a first EB 3x3 switch matrix may be coupled to the leads on the second side of second EB3x3 switch matrix by BC criss-cross extension.

The invention relates to a dynamic quality detection method for whole assembly of automobile products. The method comprises the following steps: N assembly welding or bolt junction points between the chassis component and the automobile body component of the automobile product are selected as standard detection points, and the dynamic rigidity of the assembly coupling junction interface where the N detection points are located form a complex matrix (Kd); excitation test is performed on the positions of the standard detection points, the matrix element of a frequency response function of test signals is recorded, and a standard value (Kd)0 is calculated; excitation test is performed on the automobile products of the same model number, the evaluation index value (Kd)n of the nth detected automobile product is calculated, the absolute value of difference value between the evaluation index value (Kd)n and the standard value (Kd)0 is calculated according to the formula that delta = |(Kd)n - (Kd)0 |; and if the ith diagonal entry magnitude of the absolute value is smaller than a reference value, the dynamic quality of the ith welding of the automobile product is regarded as excellent, otherwise, the dynamic quality of the ith welding of the automobile product is regarded as poor or moderate-level. Through the dynamic quality detection method, the dynamic quality of the machine assembly of the automobile products can be directly detected and evaluated.

The central controlled distributed scalable virtual machine (“CCDSVM”) of the present invention can be expanded across network domains such as Intranet and Internet, and thousands of systems in the virtual server can be organized into multiple groups (service pools) with a multi-layered hierarchy. The CCDSVM includes at least a control system to control and organize a management pool that comprising a plurality of middle level control systems, and each middle control system can control a service pool that comprising a plurality of system units. In addition, different privileged users can login different level of the control system to further centralized access the permitted system units in each pool. Specially, the present invention including a method of supporting of web folder tree and a method of supporting web based multi-tasking to enhance the manageability and operations of the CCDSVM.

The present invention provides a video human behavior recognition method based on a significant trajectory and time-space evolution information. According to the method, the optical flow information in a video is fully utilized, on the basis of improving a dense trajectory, through defining the static significance and dynamic significance of the trajectory, with a linear fusion mode, the combined significance of the trajectory is obtained through calculation, thus a background movement trajectory is effectively removed, and a foreground movement trajectory is extracted. For a problem that the rich middle and high level semantic information in a behavior video is ignored by a traditional representation method based on a low-level visual characteristic, the invention provides middle level visual characteristic expression which is a trajectory beam, human body behavior time-space evolution information is extracted to be a video characteristic expression, the background trajectory is removed effectively, the foreground movement trajectory is extracted, and the recognition effect of an algorithm is improved significantly.

An FPGA architecture has top, middle and low levels. The top level of the architecture is an array of the B16x16 tiles arranged in a rectangular array and enclosed by I / O blocks on the periphery. On each of the four sides of a B16x16 tile, and also associated with each of the I / O blocks is a freeway routing channel. A B16x16 tile in the middle level of hierarchy is a sixteen by sixteen array of B1 blocks. The routing resources in the middle level of hierarchy are expressway routing channels M1, M2, and M3 including groups of interconnect conductors. At the lowest level of the semi-hierarchical FPGA architecture, there are block connect (BC) routing channels, local mesh (LM) routing channels, and direct connect (DC) interconnect conductors to connect the logic elements to further routing resources. Each B1 block includes four clusters of devices. Each of the four clusters includes first and second LUT3s, a LUT2, and a DFF . Each of the LUT3s have first, second, and third inputs and a single output. Each of the LUT2s have first and second inputs and a single output. Each DFF has a data input and a data output. In each of the clusters the outputs of the LUT3s are muliplexed to the input of DFF, and symmetrized with the output of the DFF to form first and second outputs of each of the clusters.

The invention provides a multilevel content description-based image classification method. The method comprises the following steps of: 1) presetting a training image set; obtaining each image area hiberarchy tree by multilevel image segmentation; and extracting low-level features of each node area in the image area hiberarchy tree; 2) structuring a visual vocabulary by a low-level feature set ofa training image set area; mapping the image area hiberarchy tree to middle-level image features according to the visual vocabulary to obtain multilevel content description of a training image set; and 3) establishing an image classification model based on the multilevel content description of the training image set; and realizing the classification of images to be classified according to the image classification model. In the method, a multilevel segmentation area of the images is adopted; on one hand, the completeness of the image content description is enhanced; and on the other hand, the robustness of the over-segmentation and the under-segmentation of the images are enhanced. Therefore, more effective image description can be obtained to achieve higher image classification accuracy.

The invention discloses a multilevel semantic feature-based face feature extraction method and recognition method. The method includes the following steps that: 1) organ areas of each image in a facial image set A are divided; 2) bottom-level features of each organ are extracted and clustered; two clusters are extracted from clustering results and are adopted as positive and negative samples, and the positive and negative samples are trained in a paired combination manner such that a classifier set can be obtained, and the results of discrimination which is performed on the bottom-level features by the classifier set are united so as to obtain the middle-level features of the organ; the images in the A are the classified according to tags; any two classifications are selected from classification results of the tags and are adopted as positive and negative samples, and the positive and negative samples are trained in a paired combination manner such that a classifier set can be obtained, and the results of classification and discrimination which are performed on all the middle-level features in the A by the classifier set are united so as to obtain high-level features of the tags; the bottom-level features, the middle-level features and the high-level features are adopted to construct face features of the images; face features Vq are generated for any image q to be searched; and the face features Vq are matched with the face features in the A, and query results are returned. With the multilevel semantic feature-based face feature recognition method and recognition method adopted, recognition accuracy and stability can be improved.