4076 results about "Data class" patented technology

The information management system disclosed enables caregivers to make better decisions, faster, using aggregated genetic and phenotypic data. The system enables the integration, validation and analysis of genetic, phenotypic and clinical data from multiple subjects who may be at distributed facilities. A standardized data model stores a range of patient data in standardized data classes that encompass patient profile information, patient symptomatic information, patient treatment information, and patient diagnostic information including genetic information. Data from other systems is converted into the format of the standardized data classes using a data parser, or cartridge, specifically tailored to the source system. Relationships exist between standardized data classes that are based on expert rules and statistical models. The relationships are used both to validate new data, and to predict phenotypic outcomes based on available data. The prediction may relate to a clinical outcome in response to a proposed intervention by a caregiver. The statistical models may be inhaled into the system from electronic publications that define statistical models and methods for training those models, according to a standardized template. Methods are described for selecting, creating and training the statistical models to operate on genetic, phenotypic and clinical data, in particular for underdetermined data sets that are typical of genetic information. The disclosure also describes how security of the data is maintained by means of a robust security architecture, and robust user authentication such as biometric authentication, combined with application-level and data-level access privileges.

Conventional file-based engineering design data for an engineering model are represented by a plurality of components. Each component has a unique identifier, a set of fields, each field having a data type and a data value, and a program which interprets and modifies the fields. The plurality of components are stored in a repository of a server. The repository also stores a history of any changes made to the components. A plurality of client computers are bidirectionally connected to the server. Each client computer may obtain the current version of the components and may send locally edited versions of the components back to the server to replace the current versions in the repository. At the client computer, the user interacts with the components using conventional file-based software. Before locally edited versions of the components are committed to the server to replace the current versions, a synchronization and merging process occurs whereby the latest version of the components are downloaded to the client computer and are compared to the locally edited version of the components to detect resolvable (compatible) and unresolvable (incompatible) conflicts therebetween. The commit process is performed only if no unresolvable conflicts exist between the two versions of the components. To facilitate translation between file-based data and components, a schema is written to "wrap" each of the engineering file formats. Each schema is a set of classes that capture all of the information in the file-based data.

A flash drive has increased endurance and longevity by reducing writes to flash. An Endurance Translation Layer (ETL) is created in a DRAM buffer and provides temporary storage to reduce flash wear. A Smart Storage Switch (SSS) controller assigns data-type bits when categorizing host accesses as paging files used by memory management, temporary files, File Allocation Table (FAT) and File Descriptor Block (FDB) entries, and user data files, using address ranges and file extensions read from FAT. Paging files and temporary files are never written to flash. Partial-page data is packed and sector mapped by sub-sector mapping tables that are pointed to by a unified mapping table that stores the data-type bits and pointers to data or tables in DRAM. Partial sectors are packed together to reduce DRAM usage and flash wear. A spare/swap area in DRAM reduces flash wear. Reference voltages are adjusted when error correction fails.

A hierarchal data management system for a storage device includes an entity relationship discover to generate meta data from a business object, a file manager to create a partition based on the metadata, a data mover to generate a logical partitioning key and to store the logical partitioning key in the metadata for the partition. The file manager includes a data management policy to define a data class and a storage policy to map the data class to the storage device to form a partition table.

A system and method for parsing an electronic media database structure to produce tagged data that preserves the content, links, and electronic media structure. In particular, HyperText Markup Language (HTML) data is generated as an Interactive Electronic Technical Manual (IETM) (home page) linked into a relative structure of Web pages to support IETM deployment. An extraction process assesses the functionality associated with each node designated for presentation and builds a virtual Web, based on attributes stored in the IETM database. A series of Web pages with links that hierarchically presents IETM data at run time is produced. The method supports a data warehousing strategy that converts any data type eligible within the relational database. This expands support across multiple types of technical and engineering data. The preferred implementation utilizes a relative addressed pure HTML solution viewable in standard Web browsers. This open system implementation is cross platform and infrastructure independent, requiring no special server software. Retaining the hierarchical structure dictated by the relational database in HTML output enhances the supportability and maintainability of the Web implementation. Updates to this Web implementation can be incrementally applied within the hierarchy (small sections of data) or the entire logical sections of Web data.

Methods for training machines to categorize data, and/or recognize patterns in data, and machines and systems so trained. More specifically, variations of the invention relates to methods for training machines that include providing one or more training data samples encompassing one or more data classes, identifying patterns in the one or more training data samples, providing one or more data samples representing one or more unknown classes of data, identifying patterns in the one or more of the data samples of unknown class(es), and predicting one or more classes to which the data samples of unknown class(es) belong by comparing patterns identified in said one or more data samples of unknown class with patterns identified in said one or more training data samples. Also provided are tools, systems, and devices, such as support vector machines (SVMs) and other methods and features, software implementing the methods and features, and computers or other processing devices incorporating and/or running the software, where the methods and features, software, and processors utilize specialized methods to analyze data.

A method and system for persisting an object in a relational database schema by creating a new relational table at application program run-time for each class of objects to be persisted. The method may generate a schema map object for each class of objects to be persisted. The schema map object may be generated in response to the first transaction in which an object of a certain class is to be persisted and remains in memory for persisting, querying, restoring or deleting objects of that class. The schema map object determines the fields of each class of objects to be persisted, defines one or more columns in the table in accordance with the data types of the fields, and controls the passing of data between the table and the object fields.

A relativity controller is a scroll bar/window combination that provides a way to see data in relation to both the context of its wholeness and the salience of its contents. To accomplish this, the linear density or other appearance of the scroll bar (acting as a ruler or scale) varies with the density of the document salience (as indicated by different kinds of annotations or marks). It also provides a way to zoom between perspectives. This is usable on many different data types: including sound, video, graphics, calendars and word processors.

The invention provides methods and apparatus supporting a multi-pass video structure for slice data. An apparatus includes an encoder (300) for encoding at least one syntax data element related to at least two partitions of at least a portion of a picture. The at least one syntax element is encoded within a multi-pass syntax structure. The at least one syntax element belongs to a given class of data. The encoder (300) encodes the at least one syntax data element with respect to all partitions of at least the portion of the picture prior to encoding a next class of data, wherein later coded data classes, including the next class, have at least one of an explicit coding and an implicit coding of at least one of a casual dependency and a non-casual dependency with respect to earlier coded data classes coded earlier than the next class.

This patent concerns novel technology for detection of zero-day data classes for domains with high-dimensional mixed continuous/discrete feature spaces, including Internet traffic. Assume there is a known-class database available for learning a null hypothesis that a given new batch of unlabeled data does not contain any data from unknown/anomalous classes. A novel and effective generalization of previous parsimonious mixture and topic modeling methods is developed. The novel unsupervised anomaly detector (AD) acts on a new unlabeled batch of data to either identify the statistically significant anomalous classes latently present therein or reject the alternative hypothesis that the new batch contains any anomalous classes. The present AD invention can be applied in an on-line setting. Labeling (by a human expert or by other means) of anomalous clusters provides new supervised data that can be used to adapt an actively learned classifier whose objective is to discriminate all the classes.

Event data associated with possible terrorist activities occurring at geographically-dispersed locations is monitored and analyzed. Event data collected from the locations is delineated by one or more data classes. Statistical analyses performed on the event data are based on one of a number of unique time periods or blocks. Results of the statistical analyses are used in the performance of a number of correlations in order to identify patterns occurring in the data classes and/or correlations between the data classes.