Abstract: A mechanism is provided for improving the efficiency of multiple smaller direct memory access transfers. The mechanism uses one input buffer and a small result buffer, or some temporary variables, to temporarily store computation results. The mechanism performs a computation on a segment of data in the input buffer and stores the result in the temporary result buffer. The mechanism then copies the result back into the input buffer. As such, the mechanism uses the input buffer as both an input buffer and a results buffer. The mechanism then performs a direct memory access transfer on the segment of the input buffer that contains the computation result and then performs a computation on the next segment of the input buffer. The mechanism then repeats this process until the entire input buffer has been processed.

Abstract: A system, method and computer program product for seismic imaging implements a seismic imaging algorithm utilizing Reverse Time Migration technique requiring large communication bandwidth and low latency to convert a parallel problem into one solved using massive domain partitioning. Several aspects of the imaging problem, including very regular and local communication patterns, balanced compute and communication requirements, scratch data handling and multiple-pass approaches. The partitioning of the velocity model into processing blocks allows each sub-problem to fit in a local cache, increasing locality and bandwidth and reducing latency.

Abstract: A system and method implementing a hierarchical approach to RTM (Reverse Time Migration) seismic imaging at different granularity in space and time. An RTM seismic imaging algorithm utilizes RTM technique to convert a parallel problem into one solved using massive domain partitioning. In the method, a coarse-grain grid for the 3D volume of the geological subsurface structure under investigation is initially processed, permitting the RTM imaging process to be performed faster and produces lower level seismic image for inspection. Criteria are then applied to the first level of seismic image to determine whether to reject the image or whether a finer resolution seismic imaging is needed. In the case of finer resolution is needed, RTM resolution for the target volume is adjusted accordingly and RTM imaging process is applied with the new resolution. The process is repeated until either the image is accepted or rejected.

Abstract: A system, method and computer program product for seismic imaging implements a seismic imaging algorithm utilizing Reverse Time Migration technique requiring large communication bandwidth and low latency to convert a parallel problem into one solved using massive domain partitioning. Several aspects of the imaging problem are addressed, including very regular and local communication patterns, balanced compute and communication requirements, scratch data handling and multiple-pass approaches. The partitioning of the velocity model into processing blocks allows each sub-problem to fit in a local cache, increasing locality and bandwidth and reducing latency. The RTM seismic data processing utilizes data that includes combined shot data, i.e., shot data selected from amongst a plurality of shots that are combined at like spatial points of the volume.

Abstract: A system, method and computer program product for seismic imaging implements a seismic modeling algorithm utilizing Forward Wave Inversion technique for revising Reverse Time Migration models used for sub-surface modeling. The technique requires large communication bandwidth and low latency to convert a parallel problem into one solved using massive domain partitioning. The partitioning of a velocity model into processing blocks allows each sub-problem to fit in a local cache, increasing locality and bandwidth and reducing latency. The RTM seismic data processing utilizes data that includes combined shot data, i.e., shot data selected from amongst a plurality of shots that are combined at like spatial points of the volume. An iterative approach is applied such that the correction term RTM generates at each iteration in the iterative approach is used for refining the model, and the updated model is used for generating a further refined RTM model.

Abstract: A mechanism is provided for improving the efficiency of multiple smaller direct memory access transfers. The mechanism uses one input buffer and a small result buffer, or some temporary variables, to temporarily store computation results. The mechanism performs a computation on a segment of data in the input buffer and stores the result in the temporary result buffer. The mechanism then copies the result back into the input buffer. As such, the mechanism uses the input buffer as both an input buffer and a results buffer. The mechanism then performs a direct memory access transfer on the segment of the input buffer that contains the computation result and then performs a computation on the next segment of the input buffer. The mechanism then repeats this process until the entire input buffer has been processed.

Abstract: A system and method implemented by a computer for performing query based electronic document retrieval implementing a Markov process model adapted for determining a relationship or relevance between documents. The system ranks documents for retrieval based on their relevance measure. The model calculates the measure of relevance that a document from a given database is relevant to a given query. The method learns the Markov models mixture coefficients from the document database so as to maximize the relevance measure of the documents being retrieved. The method requires only that a similarity measure, D(d,d?), between two documents be specified. Any existing method may be used for generating a model that is at least as good as the chosen similarity measure.

Abstract: The present invention relates to a method, computer program product and system for the compression of a probability table and the reconstruction of one or more probability elements using the compressed data and method. After determining a probability table that is to be compressed, the probability table is compressed using a first probability table compression method, wherein the probability table compression method creates a first compressed probability table. The first compressed probability table contains a plurality of probability elements. Further, the probability table is compressed using a second probability table compression method, wherein the probability table compression method creates a second compressed probability table. The second compressed probability table containing a plurality of probability elements.

Abstract: The present invention relates to a method, computer program product and system for the compression of a probability table and the reconstruction of one or more probability elements using the compressed data and method. After determining a probability table that is to be compressed, the probability table is compressed using a first probability table compression method, wherein the probability table compression method creates a first compressed probability table. The first compressed probability table contains a plurality of probability elements. Further, the probability table is compressed using a second probability table compression method, wherein the probability table compression method creates a second compressed probability table. The second compressed probability table containing a plurality of probability elements.

Abstract: The present invention relates to a method, computer program product and system for the compression of a probability table and the reconstruction of one or more probability elements using the compressed data and method. After determining a probability table that is to be compressed, the probability table is compressed using a first probability table compression method, wherein the probability table compression method creates a first compressed probability table. The first compressed probability table contains a plurality of probability elements. Further, the probability table is compressed using a second probability table compression method, wherein the probability table compression method creates a second compressed probability table. The second compressed probability table containing a plurality of probability elements.

Abstract: A system and method for automatically providing quality assurance for user enrollment in a recognition system. Advantageously, the quality a new enrollment (i.e., a newly trained user-dependent prototype) is assessed before the new enrollment is accepted in place of a current enrollment. This quality check is performed by decoding stored user test data using the new enrollment, comparing the decoding results of the new enrollment to the known script used to generate the test data to obtain an accuracy score for the new enrollment, and then comparing the accuracy score for the new enrollment with an accuracy score of a previous qualified enrollment (or, in the case where there is no previous, qualified enrollment, to the accuracy of the speaker independent model). If the decoding results of the new enrollment are acceptable, the new enrollment will be used for recognition; otherwise it will be rejected and discarded.

Abstract: Systems and methods for reordering unconstrained handwriting data using both spatial and temporal interrelationships prior to recognition, and for spatially organizing and formatting machine recognized transcription results. The present invention allows a machine recognizer to generate and present a full and accurate transcription of unconstrained handwriting in its correct spatial context such that the transcription output can appear to “mirror” the corresponding handwriting.

Abstract: A handwriting recognition system and method whereby various character sequences (which are typically “slurred” together when handwritten) are each modelled as a single character (“compound character model”) so as to provide increased decoding accuracy for slurred handwritten character sequences. In one aspect of the present invention, a method for generating a handwriting recognition system having compound character models comprises the steps of: providing an initial handwriting recognition system having individual character models; collecting and labelling a set of handwriting data; aligning the labelled set of handwriting data; generating compound character data using the aligned handwriting data; and retraining the initial recognition system with the compound character data to generate a new recognition system having compound character models.

Abstract: Systems and methods for reordering unconstrained handwriting data using both spatial and temporal interrelationships prior to recognition, and for spatially organizing and formatting machine recognized transcription results. The present invention allows a machine recognizer to generate and present a full and accurate transcription of unconstrained handwriting in its correct spatial context such that the transcription output can appear to “mirror” the corresponding handwriting.

Abstract: A data recognition system and method which allows a user to select between a “default recognition” mode and a “constrained recognition” mode via a user interface. In the default recognition mode, a recognition engine utilizes predetermined default recognition parameters to decode data (e.g., handwriting and speech). In the constrained recognition mode, the user can select one or more of a plurality of recognition constraints which temporarily modify the default recognition parameters to decode uncharacteristic and/or special data. The recognition parameters associated with the selected constraint enable the recognition engine to utilize specific information to decode the special data, thereby providing increased recognition accuracy.

Abstract: Keyword selection methods for use with handwriting recording devices such as a personal digital notepad (PDN) which provide robust keyword selection by making stroke membership and selection more flexible and, therefore, less prone user error/variability. In one aspect of the present invention, a method for selecting a keyword in a handwriting recording device comprises the steps of invoking a keyword selection mode writing bounding strokes around handwritten strokes selected by a user for designation as a keyword; defining a bounding region as the area contained within the bounding strokes; and determining keyword membership of a recorded stroke based on a relation between the recorded stroke and the defined bounding region. Keyword membership may be determined by including only those recorded strokes which fall entirely within the bounding region.

Abstract: Systems and methods for reordering unconstrained handwriting data using both spatial and temporal interrelationships prior to recognition, and for spatially organizing and formatting machine recognized transcription results. The present invention allows a machine recognizer to generate and present a full and accurate transcription of unconstrained handwriting in its correct spatial context such that the transcription output can appear to “mirror” the corresponding handwriting.

Abstract: System and methods for visually displaying page information in a handwriting recording device such as a personal digital notepad (PDN) device, in which constraints exist which limit the size of a user interface display (e.g. LCD). Various methods allow a user to view detailed page information by selecting one or more available display modes which display the selected information using one or more dynamic icons. In addition, the user can view (via the display) selected portions of handwriting content of a given electronic page, thereby affording the user the opportunity to synchronize the stored handwriting data with the handwritten text.

Abstract: An apparatus and method for providing improved data classification and, in particular, an apparatus and method for improved handwriting data recognition which enables handwriting recognition devices to robustly handle and recover from the problems associated with the omission of characters from collected handwriting samples. In one aspect, a data classification apparatus comprises: means for inputting a plurality of data, the plurality of data including one of data to be recognized, generic data and user-specific data; means for augmenting the user-specific data with the generic data to generate augmented user-specific data; means for training the data classification apparatus with the augmented user-specific data to generate training data; and means for recognizing the data to be recognized in accordance with the training data.

Abstract: A method of training a writer dependent handwriting recognition system with handwriting samples of a specific writer comprises the steps of: capturing the handwriting samples of the specific writer; segmenting the handwriting samples of the specific writer; initializing handwriting models associated with the specific writer from the segmented handwriting samples; and refining the initialized handwriting models associated with the specific writer to generate writer dependent handwriting models for use by the writer dependent handwriting recognition system. Preferably, the method also comprises the step of repeating the refining step until the writer dependent handwriting models yield recognition results substantially satisfying a predetermined accuracy threshold.