143 results about "Elastic network" patented technology

A method for securing an IT (information technology) system using a set of methods for knowledge extraction, event detection, risk estimation and explanation for ranking cyber-alerts which includes a method to explain the relationship (or an attack pathway) from an entity (user or host) and an event context to another entity (a high-value resource) and an event context (attack or service failure).

A test network is provided to test updates to configurations and resources of a distributed platform and to warm servers prior to their deployment in the distributed platform. The test network tests and warms using real-time production traffic of the distributed platform in a manner that does not impact users or performance of the distributed platform. At least one distributed platform caching server passes content requests that it receives to the test network using a connectionless protocol. The test network includes a test server that is loaded with any of a configuration or resource under test or whose cache is to be loaded prior to the server's deployment into the distributed platform. The test network also includes a replay server that receives the requests from the caching server, distributes the requests to the test server, and monitors the test server responses.

The invention provides an elastic network interface realization method and system. The method comprises the following steps of: polymerizing one or a plurality of polymerized ports on one or a plurality of nodes into one distributed link aggregation group (DLAG), and realizing a distributed elastic network interface by the DLAG. According to the elastic network interface realization method and system disclosed by the invention, the problem that normal flow transmission in any network can not be guaranteed by the traditional looped network and other protection technologies is solved, the normal operation of service in the network is effectively guaranteed, and the network interface reliability and the link use ratio are improved.

An improved ship target detection method based on YOLO V2 comprises the following steps: (1) making a ship data set according to a VOC data set format; (2) taking an improved Darknet-19 Network as thebasic network to serve as a YOLO V2 feature extractor and a classification network, adding additional auxiliary network layer in the improved Darknet-19 to form a complete YOLO V2 target detection network; (3) training the model based on the network structure; (4) using the trained model to detect the ship target and evaluate the model. Effect 1: the method replaces the traditional non-imaging technology and imaging technology of ship detection and avoids the influence of external interference on ship detection, and the real-time and accuracy based on YOLO V2 can meet the requirements of real-time monitoring and accurate detection of marine monitoring system. Effect 2: aiming at the problem of small target detection, the network is improved to solve the problem of small target detection in the field of target detection to a large extent.

The invention relates to a deep neural network target detection method integrated with a pixel-level attention mechanism. The deep neural network target detection method comprises the following steps:collecting a training sample image; converting data in the collected image data set into a format required by training the deep convolutional neural network through preprocessing, and performing dataenhancement to improve the training effect of the neural network; designing a deep convolutional neural network structure integrated with a pixel-level attention mechanism, the network structure being used for receiving an input image and outputting bounding box regression information and category information to an object in the image: the network structure comprising two parts, one part being abasic network for preliminarily extracting features; the other part being a plurality of cascaded convolutional layers or downsampling layers added at the tail end of the basic network and being usedfor extracting convolutional feature maps with different scales and fusing the multi-scale feature maps with a pixel-level attention mechanism; and training.

The present invention discloses an elastic network bandwidth service system based on cloud. The elastic network bandwidth service system supports the internet protocol IPV6 addresses and IPV4 addresses, supports the separated usage of the IP addresses and the elastic calculating units, and comprises a man-machine interface management system, an integrated DNS domain name service on-line system capable of being accessed by any network browser, an elastic load balance service system and a content acceleration network service system. The elastic network bandwidth service system totally supports the elastic network bandwidth, the elastic calculation and the elastic storage services, and possesses a wide market application prospect.

The invention discloses a novel genotype analysis method based on multimodal brain images. With utilization of information, including a structural image and a functional image, of two kinds of modes, regression on the rs429358 locus genotype linked to the Alzheimer's disease closely is realized. The method comprises: extracting voxel features from a brain structure images and extracting connecting network features from a brain function image; carrying out feature extraction on the two kinds of features by using an elastic network and keeping brain area and network connection with a high association degree; and then carrying out fusion and genotype regression on selected nodes and side attributes by using a multi-kernel support vector. The method has the following advantages: for the brain image with the complicated structure and functions and genotype data, a novel regression analysis method for a single locus genotype based on structural and functional multimodal brain images is put forward; the analysis effect is good; and complementary information of the two modes is utilized fully.

The invention discloses a preparation method of a graphene-coated silicon-carbon composite anode material and a lithium ion battery including the anode. The preparation method of the carbon composite anode includes the steps of: ultrasonic-dispersing nano silicon material, graphite, graphene, graphite oxide, an organic high-molecular polymer and a solvent to prepare silicon-carbon composite anode slurry; coating a metal current collector with the slurry and drying the slurry to form a silicon-carbon composite anode sheet; and performing thermal treatment to the silicon-carbon composite anode sheet at 300-800 DEG C under protection of an inert gas, wherein the organic high-molecular polymer in the silicon-carbon composite anode is subjected to the thermal treatment and is cyclized, so that nano silicon anode material is tightly combined with modified graphene to form an elastic network structure, thus ensuring strength and flexibility of the electrode and ensuring certain porosity.

The invention discloses a distributed resilient network interconnection-based service bearing method and device. The method includes the following steps that: states and/or port states of inside-end systems in a distributed resilient network interconnection (DRNI) end point are synchronized between the inside-end systems; the inside-end systems detect that an event has occurred, wherein the event is used for triggering the update of inside-end systems and/or ports that bear services; the inside-end systems determine services that are affected by the event; and the inside-end systems update the inside-end systems and/or ports that bear the services according to the sequence of the inside-end systems that bear the services and the sequence of the ports that bear the services as well as the states of the inside-end systems in the end point and/or the states of the ports. By means of the distributed resilient network interconnection-based service bearing method and device of the invention, the problem of flow interrupt when faults occur in aggregated links or inside-end systems in the prior art can be solved, and influence on services which is caused by the faults can be decreased, and user experience can be improved.

A biochip has an integrated temperature sensor comprising a micro mechanical actuator (20) having a deformation dependent on temperature, and a detector (30) arranged to output a signal according to a deformation of the actuator. The actuator (comprising a thermally actuable polymer) can be formed of LC Liquid Crystal material in an elastomeric network. The detector (30) can be optical, magnetic or capacitive. The actuator can be arranged as a layer and the deformation be a curling of the layer.

According to some embodiments, system and methods are provided, comprising receiving, from a network configuration module, configuration data at a network driver of a communication network; configuring the network driver based on the received configuration data; receiving one or more data packets at the network driver from an application; determining that one or more segregation features are present in the data packet based on the received configuration data; transmitting the one or more data packets based on the one or more segregation features; and controlling one or more operations of an installed product based on the transmitted one or more data packets. Numerous other aspects are provided.

The invention is related to a method for resilient multi-paths connections between edge devices of a communication network. First are determined connection-specific traffic distribution functions for the multi-paths depending on a plausible failure pattern of active and inactive paths of the multi-path of this connection. Further is selected the traffic distribution function for a multi-path depending on the current failure pattern of active an inactive paths of the multi-path of this connection and is distributed the traffic of the connection onto the path of the corresponding multi-path pursuant to the selected traffic distribution function. An essential advantage of the invention is a significant decrease of network capacity for resilient multi-path connections. Another advantage of the invention is the short reaction time in case of an outage of one or more path of the multi-path connections.

The invention discloses a denoising method of a low-rank image, which is applied to the reconstruction of an image containing noise. By analyzing the correlation characteristics of the low-rank matrix, the denoising problem of the image is modeled as a non-linear constraint problem, and then the specific iterative steps are deduced by using an alternating direction multiplier method, thereby obtaining the image after denoising. The invention uses the truncated kernel norm to more accurately approximate the rank of the matrix and avoids the result deviation caused by the large singular value. In addition, the Frobenius norm is added to the model as a regular term, the Frobenius norm and the truncated kernel norm form an elastic network about the singular value, so that the final result is sparse and stable, so that better denoising effect can be achieved.

The invention discloses a personal credit risk evaluation method and evaluation system for large-scale unbalanced credit data. The method comprises steps that firstly, according to the acquired high-dimensional large-scale unbalanced historical credit data, a training matrix X constructed by the acquired historical data set is constructed, and the adaptive elastic network characteristic selectionalgorithm is utilized to implement dimensional reduction for the given historical credit data set; and secondly, a training sample set after dimension reduction is divided into a few of sample classesand a plenty of sample classes, the membership degree of each sample is calculated according to the cluster-like centroid distance exponential attenuation function, a weight matrix W is constructed,relevant parameters are set, and an IWELM model is utilized to implement personal credit risk evaluation. The method is advantaged in that a high-degree unbalanced problem shown by the large-scale credit data is overcome, the speed and efficiency of personal credit risk evaluation are further improved, and reliability and credibility of the evaluation result are improved.

The invention provides an imaging reconstruction method and apparatus. The method comprises: a surface fluorescence image of an imaging region is obtained; according to the surface fluorescence image, a reconstruction equation is established based on a finite element method; a reconstruction objective function is constructed by using an elastic network penalty item coefficient and the reconstruction equation; and on the basis of a near-end gradient method, iterative solution is carried out on reconstruction objective function to generate an imaging reconstruction result. With the surface fluorescence signal, balancing between sparsity and smoothness of the reconstruction target is realized by the elastic network penalty item; and on the basis of the near-end gradient lgorithm, the equation is solved to obtain a fluorescent light distribution component rapidly, so that a light source distribution image is constructed rapidly and precisely. Therefore, the reconstruction time is reduced; the resolution is improved; and the equipment hardware cost is lowered.

A method and apparatus for dynamically switching a gateway of a DRNI are provided. The method includes: synchronizing information of main and backup gateways of each portal system between a portal system of a DRNI end point and other portal systems of the present end point; the portal system detecting whether an event which triggers switching the main and backup gateways occurs or not; and updating a gateway of a service or session when the event which triggers switching the main and backup gateways is detected, a portal system in which a new main gateway of the service or session is located starting to forward the service or session via the main gateway, and a portal system in which the backup gateway of the service or session is located stopping forwarding the service or session via the backup gateway.

A resilient interface architecture may include at least two interface switches and at least two interface routers. The at least two interface switches may provide connectivity between a subnetwork and a main network. if one of the switches fails, the connectivity otherwise provided by the failed interface switch may be provided by another one of the interface switches. Each interface router may be individually coupled to at least one interface switch. The interface routers may select a transmission path between the subnetwork and the main network through the interface switches. if one of the interface routers fails, the selection of transmission paths otherwise provided by the failed interface router may be provided by another one of the interface routers.

The invention discloses a self-adaptive feature selection and time consistency robust correlation filtering visual tracking method, and relates to a computer vision technology. The elastic network andthe time consistency constraint are introduced into related filtering learning at the same time. The method has the advantages that the discriminative features can be adaptively selected to inhibit the interference features, model learning and updating can be combined together, the problems of poor discriminative property and time-dependent degradation of a traditional related filter can be effectively solved, and the robustness of the algorithm to shielding, deformation, rotation and background interference is improved. Through the elastic network and the time consistency constraint, the correlation filter adaptively selects discriminative features which are continuous in time and have regional characteristics. The derived correlation filtering learning problem can be solved through an ADMM, and the problem can be efficiently solved only through a few iterations. And better performance can be obtained, the precision is high, and the speed is high.

The invention discloses a reusable multiple-protection operating gown. The operating gown is made from fabric serving as basic fabric in a clipped mode; the fabric is made from 75D/72F low elastic network yarns, 6F conductive yarns and anti-radiation metal wires in an interwoven mode, wherein the 6F conductive yarns and the anti-radiation metal wires serve as warp yarns and weft yarns; the warp tightness of the fabric is 66.5, the weft tightness of the fabric is 41.0, the whole warp yarn quantity is 3,322 teeth, the whole weft yarn quantity is 9,968 teeth, the gram weight per square of the fabric is 118/m<2>, the weft density is 41/cm, and the low elastic network yarns comprise 96% of polyster chemical fiber filaments and 4% of composite carbon fiber components; the basic fabric is dyed through disperse dyes, and then a single face or double faces is/are coated or soaked with DuPont Teflon. According to the reusable multiple-protection operating gown, the advantages of a traditional cotton-cloth operating gown and the advantages of a disposable nonwoven operating gown are combined, a brand-new operating-gown composite fabric formula is provided, the reusable multiple-protection operating gown can be reused for multiple times, and the reusable multiple-protection operating gown has the breathable performance, the comfortable performance, the small fiber tow floccule performance and the like, and also has the water resistance function, the blood resistance function, the bacterium resistance function, the static resistance function, the radiation resistance function and the like.