82 results about "Classification procedure" patented technology

A technique is provided for implementing deep-packet inspection (DPI) services in a MPLS/VPN configured computer network. The technique employs a novel self-learning algorithm that analyzes data packets belonging to different unidirectional tunnels in the MPLS/VPN network and determines whether the analyzed data packets transport data in the same VPN. If so, the unidirectional tunnels containing the analyzed data packets are associated with a common layer-2 identification (L2ID) value. Unlike conventional flow-classification procedures, the inventive technique classifies a data packet by first associating the data packet with a L2ID value and then classifying the packet as belonging to a particular data flow based on a novel 6-tuple consisting of a conventional 5-tuple plus the packet's L2ID value. Because unidirectional tunnels corresponding to the same application data flow transport data packets having the same set of 6-tuple values, DPI services can apply application-level policies to classified data packets consistent with their 6-tuple flow classifications.

A method and system for achieving stability while reallocating resources in a logically partitioned environment. The present invention comprises Performance Enhancement Program (PEP), Classification Program (CP), System Analysis Program (SAP), and System Evaluation Program (SEP). PEP allows a user to enter several performance parameters. CP classifies each of the virtual systems in the managed system based on their workload. SAP analyses the managed system to determine the configuration of the managed system. Managed systems configurations are classified according to the reciprocity of resource allocation and the overall symmetry of the managed systems. SEP evaluates the configuration of the managed system and recommends alterations for improved performance of the managed system. The managed system will be optimized when the functional differentiator (FD) of the virtual systems is small enough to allow reallocation of resources without an unacceptable sacrifice in managed system stability.

A method for grouping IM statements together into a plurality of topics and displaying the topics in separate windows comprising a Configuration Program (CP), a Topic Creation Program (TCP), and a Statement Classification Program (SCP). The CP allows a user to configure the global options for the present invention such as designating the parties authorized to create a topic, specifying whether the topic name and/or keywords are negotiable, and specifying whether icons should be displayed with the topic name. The TCP allows a user to create a topic by specifying the topic name, selecting a statement classification method, designating keywords to be used in searching the statements, and adding an icon to the topic name. When a statement is submitted to an IM channel, the SCP places the statement into one of the topics based on the statement classification method selected in the TCP.

The present invention relates to a system and method to facilitate efficient and automated processing of messages. A bulk filter is provided to categorize one or more received messages according to a range of classification, the range spanning from at least a bulk classification of values to at least a non-bulk classification of values. A second filter is provided to further classify the received messages in order to automatically facilitate processing of the messages. The range of classification includes a continuum of values based on a likelihood that the received messages are determined to tend toward or fall within the bulk classification of values or toward/within the non-bulk classification of values. Also, the bulk filter or filters can include an adjustable threshold setting to determine or define differences between the bulk classifications and the non-bulk classifications. Various combinations of filters are possible including multiple filter arrangements, parallel arrangements, cascaded arrangements, and other arrangements to facilitate filtering and sorting of messages in order that users can more efficiently process such information in a timely manner. Applications include the enhancement of classification procedures for identifying urgent or important email from non-urgent or non-important email, with the combination of bulk-email filters with urgency or importance filters in cascaded and parallel filtering methodologies.

A system and method are provided for developing a database of body surface ECG P-wave maps for classification and localization of left-sided atrial arrhythmias. The system and method include generating and receiving P-wave data in a subject by left atrial pacing or receiving P-wave data in a subject during spontaneously occurring or induced left atrial arrhythmias; computing (e.g. potential or integral) maps of the P-wave data; classifying the maps specific to a left atrial ectopic origin; verifying the classification procedure; averaging the classified maps into mean maps; and storing and accessing the mean maps in the database. The mean maps of the P-wave data in the database can be used to automatically classify and localize P-wave data from a patient obtained during a left atrial arrhythmia such as atrial tachycardia, focal atrial fibrillation, or orthodromic atrioventricular reentrant tachycardia.

A method is provided for comparing malware or other types of computer programs, and for optionally using such a comparison method for (a) searching for matching programs in a collection of programs, (b) classifying programs, and (c) constructing a classification or a partitioning within a collection of programs. In general, there are three steps to the comparison portion: selecting and extracting tokens from a pair of programs for comparison, building features from these tokens, and comparing the programs based on the frequency of feature occurrences to produce a similarity measure. Pairwise similarity is then used for optionally searching, classifying, or constructing classification systems.

A defect is efficiently and effectively classified by accurately determining the state of overlap between a design layout pattern and the defect. This leads to simple identification of a systematic defect. A defective image obtained through defect inspection or review of a semiconductor device is automatically pattern-matched with design layout data. A defect is superimposed on a design layout pattern for at least one layer of a target layer, a layer immediately above the target layer, and a layer immediately below the target layer. The state of overlap of the defect is determined as within the pattern, over the pattern, or outside the pattern, and the defect is automatically classified.

A system and method are disclosed for performing wavelet-based local texture feature extraction and classification procedures. Image data is initially provided to include a query image and a series of test images. A feature detector calculates image parameters corresponding to the image data. The image parameters include mean absolute values, variance values, and texture angles. The feature detector utilizes the image parameters to calculate distance values that represent texture similarity characteristics between the query image and each of the test images. The feature detector then evaluates the distance values to determine one or more matching images from among the test images.

The invention provides an entity identification technology based on Weibo emotion. The entity identification technology comprises the steps that Weibo data are acquired through an api collection technology and preprocessed, wherein a Circumplex annular emotion model is used as an emotion analysis model, and four kinds of emotion keyword dictionaries are generated; Weibo data are acquired through the API collection technology, preprocessing is conducted on data and vectorization is conducted on a data set, learning and training are conducted through four machine learning algorithms, quintuplicate cross validation is conducted, and classification is conducted on the new data set through a selected optimal machine learning classification program; finally, entity extraction is conducted on the classified data.

A method and apparatus for efficiently classifying and categorizing data objects such as electronic text, graphics, and audio based documents within very-large-scale hierarchical classification trees is provided. In accordance with one embodiment of the invention, a first node of a plurality of nodes of a subject hierarchy is selected. Previously classified data objects corresponding to a selected first node of a subject hierarchy as well as any associated sub-nodes of the selected node are aggregated to form a content class of data objects. Similarly, data objects corresponding to sibling nodes of the selected node and any associated sub-nodes of the sibling nodes are then aggregated to form an anti-content class of data objects. Features are then extracted from each of the content class of data objects and the anti-content class of data objects to facilitate characterization of said previously classified data objects.

An ordered classification procedure includes receiving a packet including a plurality of packet fields having corresponding field values. At least some of the packet fields are parsed to extract at least some of the field values of the packet. The extracted field values are examined using the ordered classification procedure to classify the packet into a flow. An order of the field examinations scheduled within the ordered classification procedure to examine the field values is based at least in part on the field values themselves.

A system for organizing email comprising: (a) a modeler operable to infer a temporal sequential process from a corpus of unlabeled email messages; and (b) a categorizer operable to accept an incoming message and map the aforesaid incoming message to a transition in the aforesaid temporal sequential process.

Method for identifying an incoming vehicle on the basis of images acquired by one or more video-cameras mounted on a vehicle, comprising processing the images in order to identify light spots corresponding to the vehicle lamps, including performing a multi-scale processing procedure to extract bright spots areas from the images and maximum values of the bright spots areas. The method includes tracking positive regions corresponding to the bright spots and independently tracking the bright spots themselves. The tracking of the positive regions is preceded by a classification procedure including generating candidate regions to be classified, and training multiple classifiers, depending on an aspect ratio of the candidate region.

A computer implemented system and method are provided for refining category scores for pages of a sequence of document pages that potentially includes document boundaries. The method uses initial category scores provided by a categorizer that considers one page at a time or concatenated pairs of pages (called bipages). The category scores represent the probability that a page belongs to a particular category. The method uses anisotropic diffusion to refine the initial page category scores using the scores of neighboring pages as a function of the probability that there is a boundary between the pages. The method may be performed iteratively.

A system includes a processor and a memory for evaluating a focus status of a video camera. The system receives a video image from a video server in accordance with a predetermined schedule. A selected focus classification procedure is performed on the received video image. The focus state of the video image of the video camera is classified in accordance with the focus classification procedure and determining from the video image whether the video camera is in a state of focus. A warning count is cleared when the video image is determined to be in a state of focus and an alarm indication is set when the warning count exceeds a predetermined threshold.

The invention discloses a fall-down early warning apparatus and method for virtual reality experience, and mainly relates to the fields of machine learning and virtual reality. A pose classification program capable of identifying a pose action of a user is obtained by training through a machine learning algorithm; eigenvalues are extracted from a real-time pose of the user to serve as input data of the classification program; an output result is a real-time fall-down risk probability of the user; and when a fall-down risk is excessively high or fall-down already occurs, the apparatus gives analarm. The eigenvalues are processed by using a depth sensor with a skeleton information extraction function; 20 joint points taking a main effect during motion of a human body are extracted; and spatial vectors of the eigenvalues are selected by taking a gravity center point of the human body as an origin of coordinates, taking a vertical direction as a Z axis, taking a direction faced by the user as a Y axis and taking an arm stretching direction as an X axis. The spatial vectors of the 20 joint points of each frame of image serve as a group of eigenvalues. After the feature extraction is finished, eigenvalue data is input to the classification program, so that the fall-down risk probability can be obtained.

The invention provides an automatic angle steel feeding, overturning, machining and discharging classification device. The device comprises a feeding machine, an angle steel punching machine, a discharging channel support, a V-shaped block transferring mechanism, a discharging classification mechanism and a PLC control system; the feeding machine comprises a feeding crane frame, a winch, a cross beam, a first overturning mechanism, a second overturning mechanism, a conveying belt conveyor and an eddy current sensor; angle steel is automatically fed through the feeding machine, different adsorbed angle steel postures are automatically turned into a unified angle steel posture, and the feeding procedure is completed; the discharging channel support receives angle steel machined by the anglesteel punching machine and rotates to the discharging mechanism through the V-shaped block transferring mechanism, the discharging classification mechanism comprises a discharging crane frame, a discharging air cylinder, a barb, a classification frame, a triggering mechanism and a photoelectric switch, and the angle steel completes the discharging classification procedure through the discharging classification mechanism; and the feeding machine, the discharging channel support, the V-shaped block transferring mechanism and the discharging classification mechanism are all controlled by the PLCcontrol system. The whole process is high in automation degree, high in efficiency and low in labor cost.