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| 20080256427 | SYSTEM, METHOD, AND SERVICE FOR PROVIDING A GENERIC RAID ENGINE AND OPTIMIZER - A generic RAID engine system accepts an access request, accepts a metadata input comprising a layout description and, optionally, a plurality of resource optimization objectives, accepts a dynamic input comprising a dynamic state of an I/O stack comprising the generic RAID engine and a fault configuration of a plurality of storage devices in the I/O stack, and accepts RAID code input comprising information about the RAID code used by the I/O stack. The metadata input, the dynamic input, and the RAID code input are utilized to transform the access request into individual device reads and individual device writes such that RAID code relationships for the storage devices are maintained at all times. An optional optimizer module selects strategies that meet the resource optimization objectives. | 10-16-2008 |
| 20080270704 | CACHE ARRANGEMENT FOR IMPROVING RAID I/O OPERATIONS - The embodiments of the invention provide a method, apparatus, etc. for a cache arrangement for improving RAID I/O operations. More specifically, a method begins by partitioning a data object into a plurality of data blocks and creating one or more parity data blocks from the data object. Next, the data blocks and the parity data blocks are stored within storage nodes. Following this, the method caches data blocks within a partitioned cache, wherein the partitioned cache includes a plurality of cache partitions. The cache partitions are located within the storage nodes, wherein each cache partition is smaller than the data object. Moreover, the caching within the partitioned cache only caches data blocks in parity storage nodes, wherein the parity storage nodes comprise a parity storage field. Thus, caching within the partitioned cache avoids caching data blocks within storage nodes lacking the parity storage field. | 10-30-2008 |
| 20080270878 | CACHE ARRANGEMENT FOR IMPROVING RAID I/O OPERATIONS - The embodiments of the invention provide a method, apparatus, etc. for a cache arrangement for improving RAID I/O operations. More specifically, a method begins by partitioning a data object into a plurality of data blocks and creating one or more parity data blocks from the data object. Next, the data blocks and the parity data blocks are stored within storage nodes. Following this, the method caches data blocks within a partitioned cache, wherein the partitioned cache includes a plurality of cache partitions. The cache partitions are located within the storage nodes, wherein each cache partition is smaller than the data object. Moreover, the caching within the partitioned cache only caches data blocks in parity storage nodes, wherein the parity storage nodes comprise a parity storage field. Thus, caching within the partitioned cache avoids caching data blocks within storage nodes lacking the parity storage field. | 10-30-2008 |
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| 20080201139 | Generic framework for large-margin MCE training in speech recognition - A method and apparatus for training an acoustic model are disclosed. A training corpus is accessed and converted into an initial acoustic model. Scores are calculated for a correct class and competitive classes, respectively, for each token given the initial acoustic model. Also, a sample-adaptive window bandwidth is calculated for each training token. From the calculated scores and the sample-adaptive window bandwidth values, loss values are calculated based on a loss function. The loss function, which may be derived from a Bayesian risk minimization viewpoint, can include a margin value that moves a decision boundary such that token-to-boundary distances for correct tokens that are near the decision boundary are maximized. The margin can either be a fixed margin or can vary monotonically as a function of algorithm iterations. The acoustic model is updated based on the calculated loss values. This process can be repeated until an empirical convergence is met. | 08-21-2008 |
| 20090063126 | Validation of the consistency of automatic terminology translation - A method of determining the consistency of training data for a machine translation system is disclosed. The method includes receiving a signal indicative of a source language corpus and a target language corpus. A textual string is extracted from the source language corpus. The textual string is aligned with the target language corpus to identify a translation for the textual string from the target language corpus. A consistency index is calculated based on a relationship between the textual string from the source language corpus and the translation. An indication of the consistency index is stored on a tangible medium. | 03-05-2009 |
| 20090112573 | Word-dependent transition models in HMM based word alignment for statistical machine translation - A word alignment modeler uses probabilistic learning techniques to train “word-dependent transition models” for use in constructing phrase level Hidden Markov Model (HMM) based word alignment models. As defined herein, “word-dependent transition models” provide a probabilistic model wherein for each source word in training data, a self-transition probability is modeled in combination with a probability of jumping from that particular word to a different word, thereby providing a full transition model for each word in a source phrase. HMM based word alignment models are then used for various word alignment and machine translation tasks. In additional embodiments sparse data problems (i.e., rarely used words) are addressed by using probabilistic learning techniques to estimate word-dependent transition model parameters by maximum a posteriori (MAP) training. | 04-30-2009 |
| 20090240486 | HMM ALIGNMENT FOR COMBINING TRANSLATION SYSTEMS - A computing system configured to produce an optimized translation hypothesis of text input into the computing system. The computing system includes a plurality of translation machines. Each of the translation machines is configured to produce their own translation hypothesis from the same text. An optimization machine is connected to the plurality of translation machines. The optimization machine is configured to receive the translation hypotheses from the translation machines. The optimization machine is further configured to align, word-to-word, the hypotheses in the plurality of hypotheses by using a hidden Markov model. | 09-24-2009 |
| 20100161330 | SPEECH MODELS GENERATED USING COMPETITIVE TRAINING, ASYMMETRIC TRAINING, AND DATA BOOSTING - Speech models are trained using one or more of three different training systems. They include competitive training which reduces a distance between a recognized result and a true result, data boosting which divides and weights training data, and asymmetric training which trains different model components differently. | 06-24-2010 |
| 20100311030 | USING COMBINED ANSWERS IN MACHINE-BASED EDUCATION - Described is a technology for learning a foreign language or other subject. Answers (e.g., translations) to questions (e.g., sentences to translate) received from learners are combined into a combined answer that serves as a representative model answer for those learners. The questions also may be provided to machine subsystems to generate machine answers, e.g., machine translators, with those machine answers used in the combined answer. The combined answer is used to evaluate each learner's individual answer. The evaluation may be used to compute profile information that is then fed back for use in selecting further questions, e.g., more difficult sentences as the learners progress. Also described is integrating the platform/technology into a web service. | 12-09-2010 |
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| 20090157326 | Diagnosis and prognosis of breast cancer patients - The present invention relates to genetic markers whose expression is correlated with breast cancer. Specifically, the invention provides sets of markers whose expression patterns can be used to differentiate clinical conditions associated with breast cancer, such as the presence or absence of the estrogen receptor ESR1, and BRCA1 and sporadic tumors, and to provide information on the likelihood of tumor distant metastases within five years of initial diagnosis. The invention relates to methods of using these markers to distinguish these conditions. The invention also relates to kits containing ready-to-use microarrays and computer software for data analysis using the statistical methods disclosed herein. | 06-18-2009 |
| 20090204333 | METHODS FOR USING CO-REGULATED GENESETS TO ENHANCE DETECTION AND CLASSIFICATION OF GENE EXPRESSION PATTERNS - The present invention provides methods for enhanced detection of biological response patterns. In one embodiment of the invention, genes are grouped into basis genesets according to the co-regulation of their expression. Expression of individual genes within a geneset is indicated with a single gene expression value for the geneset by a projection process. The expression values of genesets, rather than the expression of individual genes, are then used as the basis for comparison and detection of biological response with greatly enhanced sensitivity. In another embodiment of the invention, biological responses are grouped according to the similarity of their biological profile. | 08-13-2009 |
| 20090239214 | Prognosis of breast cancer patients - The present invention relates to sets of genetic markers whose expression is correlated with prognosis of breast cancer in individuals having breast cancer. Specifically, the invention provides sets of markers whose expression patterns can be used to differentiate individuals having a good prognosis, e.g., no reoccurrence or metastasis within five years of initial diagnosis, and individuals having a poor prognosis, e.g., reoccurrence or metastasis within five years of initial diagnosis. The invention relates to methods of prognosis using these markers. The invention also relates to microarrays containing probes to these markers, and to kits containing ready-to-use microarrays and computer software for data analysis using the prognostic and statistical methods disclosed herein. | 09-24-2009 |
