3782 results about "Feature set" patented technology

A method and system for the automatic identification of audio, video, multimedia, and / or data recordings based on immutable characteristics of these works. The invention does not require the insertion of identifying codes or signals into the recording. This allows the system to be used to identify existing recordings that have not been through a coding process at the time that they were generated. Instead, each work to be recognized is “played” into the system where it is subjected to an automatic signal analysis process that locates salient features and computes a statistical representation of these properties. These features are then stored as patterns for later recognition of live input signal streams. A different set of features is derived for each audio or video work to be identified and stored. During real-time monitoring of a signal stream, a similar automatic signal analysis process is carried out, and many features are computed for comparison with the patterns stored in a large feature database. For each particular pattern stored in the database, only the relevant characteristics are compared with the real-time feature set. Preferably, during analysis and generation of reference patterns, data are extracted from all time intervals of a recording. This allows a work to be recognized from a single sample taken from any part of the recording.

A system and method for detecting malware by modeling the behavior of malware and comparing a suspect executable with the model. The system and method extracts feature elements from malware-infected applications, groups the feature elements into feature sets, and develops rules describing a malicious probability relationship between the feature elements. Using malware-free and malware-infected applications as training data, the system and method heuristically trains the rules and creates a probability model for identifying malware. To detect malware, the system and method scans the suspect executable for feature sets and applies the results to the probability model to determine the probability that the suspect executable is malware-infected.

A system and method for detecting malware on a limited access mobile platform in a mobile network. The system and method uses one or more feature sets that describe various non-executable portions of malware-infected and malware-free applications, and compares a application on the limited access mobile platform to the features sets. A match of the features in a suspect application to one of the feature sets provides an indication as to whether the suspect application is malware-infected or malware-free.

A method and system for language identification are provided. The system includes a feature set of a plurality of character strings of varying length with associated information. The associated information includes one or more significance scores for a character string for one or more of a plurality of languages. Means are provided for detecting character strings from the feature set within a token from an input text. The system uses a finite-state device and the associated information is provided as glosses at the final nodes of the finite-state device for each character string. The associated information can also include significance scores based on linguistic rules.

The present invention is directed to a method and system for use in a computing environment to present and provide access to user information. The system may include a sidebar for hosting a plurality of tiles. Applications may be minimized and inserted into the sidebar upon minimization. Selected features of the application remain available through a tile when the application is represented by a tile in the sidebar. The system may also include user interface tools for allowing a user to command placement of a selected application into the sidebar. The application may include an available feature selection module for allowing an application to provide at least a sub-set of a full feature set upon minimization. An insertion module may be provided for inserting the tile into the user interface.

Systems and methods are disclosed herein to allow a service provider supporting applications running on a client device to remotely disable the applications, features of the applications, or sessions of the applications running on the client device. The service providers may initiate the disable action automatically upon the detection of certain events on or through the client device without requiring user input. The disable action is specific for the client device. In one embodiment, the service provider collects information associated with the application and with the remote client device that runs the application to conduct one or more transactions with the service provider. The service provider determines from the collected information a feature set of the application to disable on the client device. The service provider disabling remotely the feature set of the application on the client device without affecting any other client devices that run the application.

A data access control facility is implemented by assigning personally identifying information (PII) classification labels to PII data objects, with each PII data object having one PII classification label assigned thereto. The control facility further includes at least one PII purpose serving function set (PSFS) comprising a list of application functions that read or write PII data objects. Each PII PSFS is also assigned a PII classification label. A PII data object is accessible via an application function of a PII PSFS having a PII classification label that is identical to or dominant of the PII classification label of the PII object. A user of the control facility is assigned a PII clearance set which contains a list of at least one PII classification label, which is employed in determining whether the user is entitled to access a particular function.

The invention provides systems and methods for detection, grading, scoring and tele-screening of cancerous lesions. A complete scheme for automated quantitative analysis and assessment of human and animal tissue images of several types of cancers is presented. Various aspects of the invention are directed to the detection, grading, prediction and staging of prostate cancer on serial sections / slides of prostate core images, or biopsy images. Accordingly, the invention includes a variety of sub-systems, which could be used separately or in conjunction to automatically grade cancerous regions. Each system utilizes a different approach with a different feature set. For instance, in the quantitative analysis, textural-based and morphology-based features may be extracted at image- and (or) object-levels from regions of interest. Additionally, the invention provides sub-systems and methods for accurate detection and mapping of disease in whole slide digitized images by extracting new features through integration of one or more of the above-mentioned classification systems. The invention also addresses the modeling, qualitative analysis and assessment of 3-D histopathology images which assist pathologists in visualization, evaluation and diagnosis of diseased tissue. Moreover, the invention includes systems and methods for the development of a tele-screening system in which the proposed computer-aided diagnosis (CAD) systems. In some embodiments, novel methods for image analysis (including edge detection, color mapping characterization and others) are provided for use prior to feature extraction in the proposed CAD systems.

A method and apparatus for forecasting and controlling neurological abnormalities in humans such as seizures or other brain disturbances. The system is based on a multi-level control strategy. Using as inputs one or more types of physiological measures such as brain electrical, chemical or magnetic activity, heart rate, pupil dilation, eye movement, temperature, chemical concentration of certain substances, a feature set is selected off-line from a pre-programmed feature library contained in a high level controller within a supervisory control architecture. This high level controller stores the feature library within a notebook or external PC. The supervisory control also contains a knowledge base that is continuously updated at discrete steps with the feedback information coming from an implantable device where the selected feature set (feature vector) is implemented. This high level controller also establishes the initial system settings (off-line) and subsequent settings (on-line) or tunings through an outer control loop by an intelligent procedure that incorporates knowledge as it arises. The subsequent adaptive settings for the system are determined in conjunction with a low-level controller that resides within the implantable device. The device has the capabilities of forecasting brain disturbances, controlling the disturbances, or both. Forecasting is achieved by indicating the probability of an oncoming seizure within one or more time frames, which is accomplished through an inner-loop control law and a feedback necessary to prevent or control the neurological event by either electrical, chemical, cognitive, sensory, and / or magnetic stimulation.

A system and method for providing a secure feature set distribution infrastructure for medical device management is presented. A unique association is mapped for data download between a medical device and a communications device transiently coupleable to the medical device. A configuration catalog is maintained, including operational characteristics of at least one of the medical device and the communications device. The operational characteristics as maintained in the configuration catalog are periodically checked against a database storing downloadable sets of features and one or more feature sets including changed operational characteristics are identified for distribution. The one or more feature sets are digitally signed and the one or more feature sets are provided to the communications device over a plurality of networks. The one or more feature sets are authenticated and their integrity is checked over a chain of trust originating with a trusted source and terminating at the communications device.

A 1D-CNN-based ((one-dimensional convolutional neural network)-based) distributed optical fiber sensing signal feature learning and classification method is provided, which solves a problem that an existing distributed optical fiber sensing system has poor adaptive ability to a complex and changing environment and consumes time and effort due to adoption of manually extracted distinguishable event features, The method includes steps of: segmenting time sequences of distributed optical fiber sensing acoustic and vibration signals acquired at all spatial points, and building a typical event signal dataset; constructing a 1D-CNN model, conducting iterative update training of the network through typical event signals in a training dataset to obtain optimal network parameters, and learning and extracting 1D-CNN distinguishable features of different types of events through an optimal network to obtain typical event signal feature sets; and after training different types of classifiers through the typical event signal feature sets, screening out an optimal classifier.

A system and method for performing a VM migration which manages a cluster of machines in a pool for live migration to the same feature set or behavior. In certain embodiments, machines within the pool can be configured to emulate a certain feature set to enable a VM migration amongst the similar pools. The emulation can be by either masking reporting of a feature set or enabling / disabling a feature set. The handling of emulation registers within the hardware occurs at a firmware level rather than an operating system or hypervisor level.

A method, apparatus and computer program product are provided for visually searching feature sets that are organized in a grid-like manner. As such, a feature set associated with a location-based grid area may be received. The location-based grid area may also be associated with the location of a device. After receiving query image features, a visual search may be performed by comparing the query image features with the feature set. The search results are then returned. By conducting the visual search within a feature set that is selected based upon the location of the device, the efficiency of the search can be enhanced and the search may potentially be performed by the device, such as a mobile device, itself.

A method and apparatus for defining and validating feature policies in an execution system, such as a communication system. The method includes entering user policies described in a straightforward manner (e.g. using a Web browser and user-understandable language) in such a way that they can be translated into a formal executable language. The user policies are then (translated into an executable feature language such as the IETE's CPL. The user is then either compelled or provided with an option to validate the overall feature set before the overall feature is uploaded to the execution system. If validation is selected, the features are translated from CPL into another format, such as FIAT, from which it is possible to detect common feature specification errors. That FIAT detected errors are then analyzed in a manner that is aware of the expectations and common errors of native users, and interpreted to determine possible errors as errors that are common to naïve users.

A run-time feature set of a process or a thread is generated and compared to at least one processor feature set. Each processor feature set represents zero or more optional hardware features supported by one or more processors, whereas the run-time feature set represents zero or more optional hardware features the process or thread relies upon. The comparison of the feature sets determines whether a particular process or thread may run on a particular processor, even in a heterogeneous processor environment. A system task dispatcher assigns the process or thread to execute on one or more processors indicated by the comparison as being compatible with the process or thread. When a new feature is added to the process or thread, the run-time feature set is updated and again compared to at least one processor feature set. The system task dispatcher reassigns the process or thread if necessary.

An adaptive method and apparatus for forecasting and controlling neurological abnormalities in humans such as seizures or other brain disturbances. The system is based on a multi-level control strategy. Using as inputs one or more types of physiological measures such as brain electrical, chemical or magnetic activity, heart rate, pupil dilation, eye movement, temperature, chemical concentration of certain substances, a feature set is selected off-line from a pre-programmed feature library contained in a high level controller within a supervisory control architecture. This high level controller stores the feature library within a notebook or external PC. The supervisory control also contains a knowledge base that is continuously updated at discrete steps with the feedback information coming from an implantable device where the selected feature set (feature vector) is implemented. This high level controller also establishes the initial system settings (off-line) and subsequent settings (on-line) or tunings through an outer control loop by an intelligent procedure that incorporates knowledge as it arises. The subsequent adaptive settings for the system are determined in conjunction with a low-level controller that resides within the implantable device. The device has the capabilities of forecasting brain disturbances, controlling the disturbances, or both. Forecasting is achieved by indicating the probability of an oncoming seizure within one or more time frames, which is accomplished through an inner-loop control law and a feedback necessary to prevent or control the neurological event by either electrical, chemical, cognitive, sensory, and / or magnetic stimulation.

An exemplary method includes a remote control emulation system directing a mobile device to display an emulation graphical user interface (“GUI”) on a display screen of the mobile device and directing the mobile device to emulate one or more user input devices by selectively positioning one or more interactive graphical depictions of one or more feature sets associated with the one or more user input devices within the emulation GUI. Corresponding methods and systems are also disclosed.

Methods and apparatus are provided of deriving a discrimination feature set for use in identifying biometric spoofs. True skin sites are illuminated under distinct optical conditions and light reflected from each of the true skin sites is received. True-skin feature values are derived to characterize the true skin sites. Biometric spoofs is similarly illuminated under the distinct optical conditions and light reflected from the spoofs is received. Spoof feature values are derived to characterize the biometric spoofs. The derived true-skin feature values are compared with the derived spoof feature values to select a subset of the features to define the discrimination feature set.

The present invention generally describes a method for classifying a line segment of a handwritten line into a reference feature set, wherein said handwritten line comprises one or several curves representing a plurality of symbols. First, sample data representing said handwritten line is received. Next, a sample line segment in said received sample data is identified by detecting a sample line segment start point (SLSSP) and a sample line segment end point (SLSEP). Then, a sample feature set of said identified sample line segment is determined. Finally, the determined sample feature set is matched to a reference feature set among a plurality of reference feature sets.

A method of extracting features characterising objects consists in discriminating an object from a context, the discriminating step comprising, determining the context consisting of at least two objects, choosing a topic object from the context, deriving feature sets of the topic object and the other objects in the context, judging whether there is at least one distinctive feature set in the feature sets, deriving a new feature set if there is not a distinctive feature set amongst the feature sets, and registering one of the distinctive feature sets as an outcome; and restarting the discriminating step when there exists an object which is not discriminated from the other objects. This method represents a selectionist approach to the characterisation of objects, driven by a discrimination task. There is also an apparatus putting this method into practice and a system for autonomous development of a common vocabulary by a plurality of agents incorporating the method and / or apparatus.

A method and system for the automatic identification of audio, video, multimedia, and / or data recordings based on immutable characteristics of these works. The invention does not require the insertion of identifying codes or signals into the recording. This allows the system to be used to identify existing recordings that have not been through a coding process at the time that they were generated. Instead, each work to be recognized is “played” into the system where it is subjected to an automatic signal analysis process that locates salient features and computes a statistical representation of these properties. These features are then stored as patterns for later recognition of live input signal streams. A different set of features is derived for each audio or video work to be identified and stored. During real-time monitoring of a signal stream, a similar automatic signal analysis process is carried out, and many features are computed for comparison with the patterns stored in a large feature database. For each particular pattern stored in the database, only the relevant characteristics are compared with the real-time feature set. Preferably, during analysis and generation of reference patterns, data are extracted from all time intervals of a recording. This allows a work to be recognized from a single sample taken from any part of the recording.

A method, system and wireless communications device providing location-based control of wireless communications device features provides security and nuisance avoidance for persons or organizations controlling particular areas in which the devices are not desirable for use. The location of the device is determined by triangulation or via communication of location information from the device, such as GPS information. The services provider determines whether or not the devices are within a controlled area for which features of the device are to be disabled, and disables those features if the device is in such a zone. The service provider maintains a database of zone coordinates and feature sets to disable for each zone. Features that may be disabled include: cameras, text messaging, ringers and / or voice communications. The service provider may also entirely disable a device when the device is located within a particular zone.

A system comprising a database containing first and second location elements, a feature set, and a first unique identifier associated with the second location element; a system controller coupled to the database and configured to establish the first location element with a first physical location, establish the second location element with a second physical location and associate the first unique identifier with the second location element; and a user interface coupling a first user device with the system controller, the first user device associated with the first location element; and the system controller being further configured to transmit an initiated action between the first and second user, to transmit the unique identifier to the first user in relation to the action from the second user, and to associate the first user with the second location element based on the possession of the unique identifier by the first user after transmission.

The invention relates to a method and apparatus for generating noise-attenuated feature vectors for use in recognizing speech, more particularly to a system and method providing a feature set for speech recognition that is robust to adverse noise conditions. This is done by receiving, through an input, a set of signal frames, at least some containing speech sounds, and then classifying the frames in the set of signal frames into classification groups on the basis of their energy levels. Each classification group is characterized by a mean energy value. In a specific example of implementation, the invention makes use of channel energy values to condition the frames in the set of signal frames. The frames in the set of signal frames are attenuated or noise reduced by altering the energy of the frames on the basis of the frames containing non-speech sounds. In a specific example of implementation, the invention compresses the energy of the frames in the set of signal frames such that the energy lies within a range. The invention also allows separate energy ranges to be defined for each channel.

The invention discloses a hybrid machine learning credit scoring model building method. The method comprises the steps of 1, determining client risk classification standards based on a loan client historical data set; 2, based on the loan client historical data set, obtaining a loan client data feature set through feature extraction; 3, selecting at least two model algorithms from an alternative model library, building corresponding models based on the selected algorithms, performing model performance check on the built models by adopting a K-fold cross check method, performing standard check on the models about to pass the model performance check based on model check standards, obtaining evaluation index statistical quantity values, and selecting a model type used by final modeling according to the evaluation index statistical quantity values returned by the standard check of the models; and 4, based on the algorithm corresponding to the selected model type, building a credit scoring model. The technical effect of efficiently and accurately finishing user credit evaluation through the built hybrid machine learning credit scoring model is achieved.

A method, system, and apparatus for informing a plurality of operating systems, each assigned to a separate partition within a logically partitioned data processing system, of which functions, provided by a hypervisor for creating and enforcing separation of the logical partitions, are available for use by the operating systems is provided. In a preferred embodiment, the hypervisor includes a plurality of function sets. Each function set includes a list of functions that may be called by any one of the operating systems to perform tasks for the operating systems while maintaining separation between each of the logical partitions. The hypervisor informs each of the plurality of operating systems of an enabled function set. Functions identified within the enabled function set are enabled for use by each of the plurality of operating systems and functions not identified within the enabled function set are disabled for use by each of the plurality of operating systems.

The invention provides a universal machine learning data analysis platform. The universal machine learning data analysis platform comprises an interface module, a data storage module, a preprocessing module, a feature extraction module, a feature conversion module, an algorithm module and a selection optimization module, wherein the feature extraction module extracts feature parameters from to-be-analyzed data according to the feature parameters set by a user; the feature conversion module is used for converting features set by the user to be in a representation form required by the user; the algorithm module comprises a plurality of algorithm models for the user to select and build, and the user builds at least one group of models; the selection optimization module selects out an optimal model and an optimal parameter from the built models and then stores the optimal model; and data generated by the modules is stored in the data storage module. According to the platform, the user can freely combine and use the modules and the algorithm models, and also can build a complex model and quickly and iteratively develop a novel analytic model, so that the working efficiency is greatly improved.

The embodiment of the invention provides a multi-target tracking method and system based on depth features. The method comprises the following steps: obtaining detection frame positions correspondingto targets detected in a current frame image and the depth features of the targets; based on the position of the detection frame corresponding to each target in the previous frame of image, obtainingthe prediction position of each target in the current frame by using a Kalman filter; according to the detection frame position corresponding to each target, the prediction position of each target inthe current frame, the depth feature of each target and the depth feature set of each tracker, performing cascade matching on the detection frame corresponding to each target and the tracker by usinga Hungarian algorithm; And calculating an IOU distance matrix between the detection frame on the non-cascade matching and the tracker to be matched, and performing IOU matching between the detection frame and the tracker by using a Hungarian algorithm based on the IOU distance matrix to obtain a final matching set. According to the embodiment of the invention, the target tracking effect under theshielding condition can be effectively improved, and the number of times of ID switching is reduced.

A translator, system, and method of translation is provided for translating a source file in a source format to a target file in a target format. A feature identifier determines a feature set of the source file, and a feature writer writes the feature set into the target file in the target format. Optionally, the feature identifier may include a front-end lookup table to map code fragments of the source file to a list of features. The feature writer may include a back-end lookup table to map the feature set to code fragments of the target file format.

Systems and methods for threat detection in a network are provided. The system obtains recoils for entities that access a network. The records include attributes associated with the entities. The system identifies features for each of the entities based on the attributes. The system generates a feature set for each of the entities. The feature set is generated from the features identified based on the attributes of each of the entities. The system forms clusters of entities based on the feature set for each of the entities. The system classifies each of the clusters with a threat severity score calculated based on scores associated with entities forming each of the clusters. The system determines to generate an alert for an entity in a cluster response to the threat severity score of the cluster being greater than a threshold.