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208 results about "Speed of processing" patented technology

Speed of processing is a measure of the average time it takes to process a new claim or a change in circumstance of an existing claimant. The Housing Benefit speed of processing statistics show new claims and changes of circumstances separately and do not include a combined measure.

Method and equipment for full frequency domain digital hearing aid

InactiveCN101593522AProcessing speedSolving Hearing Impairment ProblemsSpeech recognitionDeaf-aid setsVoice frequencyDynamic range
The embodiment of the invention provides a method for full frequency domain digital hearing aid, which comprises the following steps: firstly, acquiring input voice signals of front and back two microphones and performing framing, Fourier transformation and voice scene type recognition; secondly, when voice is mixed with noises, performing noise detection of subframe voice frequency domain signals, beamforming of the two microphones, wind noise processing and inhibition of other noises, compacting the dynamic ranges of frequency domains and inhibiting acoustic feedback; and finally performing the Fourier transformation and overlap-add to obtain output voice signals. The embodiment of the invention also discloses equipment for full frequency domain digital hearing aid. Through the proposal provided by the embodiment of the invention, the problem that the prior digital hearing aid focuses on solving only one aspect of hearing disorder rather than comprehensively take all factors influencing use effect into consideration is solved. Meanwhile, the embodiment of the invention provides a proposal for full frequency domain digital hearing aid. The method, the equipment and proposal have the advantages of quick processing, less resource occupation, low energy consumption and the like.
Owner:TSINGHUA UNIV

Caching optimizing method of internal storage calculation

The invention provides a caching optimizing method of internal storage calculation. The method includes the steps that monitoring codes are inserted into a Spark source program, and dynamic semantic analysis is performed on an application program to construct a DAG; out-degrees of all vertexes in the DAG are calculated, RDDs of the vertexes of which the out-degrees are larger than one are screened, and the screened RDDs are RDDs needing to be cached to an internal storage; according to a greedy algorithm, the execution sequence of Action is adjusted so that the access sequence of RDD data calculation can be optimized; the weights of the RDDs are calculated, and the replaced RDDs in the internal storage are determined according to an internal storage replacement algorithm; it is determined how to process the replaced RDDs according to a multi-level caching algorithm. By the utilization of the caching optimizing method of internal storage calculation, a programmer does not need to examine and weigh internal storage using and display the RDDs of the appointed loading internal storage in the process of programming, programming loads of the programmer are reduced, meanwhile, the utilization rate of the internal storage is improved, and then the speed of processing big data is increased.
Owner:清能艾科(深圳)能源技术有限公司

Hierarchical traffic sign identification method based on quick dichotomous convolutional neural network

InactiveCN108009518AFast classification accuracyProcessing speedCharacter and pattern recognitionNeural architecturesComputational visualisticsSpeed of processing
The invention belongs to the technical fields of computer application and computer vision and provides a hierarchical traffic sign identification method based on a quick dichotomous convolutional neural network. According to the method, a quick dichotomous convolutional neural network structure is designed to relieve the problems of a large calculated quantity and time consumption in the convolution process, and a hierarchical classification algorithm based on the quick convolutional neural network is proposed. According to specific application, at a rough classification stage, a traffic signimage is preprocessed to obtain a region of interest first, and then the region of interest is input into the quick dichotomous convolutional neural network and roughly divided into a plurality of large categories; and at a fine classification stage, traffic signs are preprocessed again according to characteristics of all the categories, the quick dichotomous convolutional network is further utilized to perform fine classification on the processed signs, and a final result is obtained. The result shows that the proposed algorithm has a high classification correct rate, meanwhile has a high processing speed and is more suitable for a traffic sign identification system with a high instantaneity requirement.
Owner:DALIAN UNIV OF TECH

Active contour model based method for segmenting mammary gland DCE-MRI focus

ActiveCN103337074AReduce complexityAccurately identify fuzzy boundariesImage analysisContour segmentationSpeed of processing
An active contour model based method for segmenting mammary gland DCE-MRI focus belongs to the field of medical image segmentation and comprises the following steps: obtaining mammary gland DCE-MRI image sequence data by MRI scanning equipment; manually selecting a region of interest; automatically obtaining subtracted size of interest, active contour segmenting focus and visually display focus. According to the invention, based on the features that statistical distributions of mammary gland DCE-MRI image backgrounds are consistent and internal distributions in the focus are different, an edge stopping function of the active contour model is designed, thereby realizing reliable segmentation of the focus and effectively avoiding edge outleakage phenomenon; during the model evolutionary process, re-initialization of a signed distance function is not required, so that the real-time performance of the system is higher. The method has a lower requirement on manual operation in implementation, is high in intelligent degree, low in data storage space requirement, and quick in processing speed, and can effectively obtain comprehensive and steric space information of the focus through three-dimensional angle segmentation, which facilitates the multi-angle observation and analysis of the focus by a doctor.
Owner:DALIAN UNIV OF TECH

An intelligent classification method of complaint work order based on convolution neural network

The invention discloses an intelligent classification method of a complaint work order based on a convolution neural network. The invention comprises the following steps: step S1, collecting the textdata of the complaint work order, and constructing the text data set of the work order; step 2, performing word segmentation and cleaning on that text data of the complaint work order; 3, extract feature words and carry out quantization processing; step 4, train a convolution neural network to construct a classification model; Step S5: word segmentation and cleaning of the complaint work order text data to be classified and tested; Step S6: Converting the complaint work order text data to be classified and tested into vector representation; Step S7: Input the vector representation into the classification model. The invention realizes intelligent classification of the complaint work order by collecting the text data of the complaint work order in batch, cleaning and pretreating the data, training the classification model through the convolution neural network, inputting the vector representation into the analysis model, accelerating the processing speed of the complaint work order, andimproving the customer satisfaction and the service quality.
Owner:USTC SINOVATE SOFTWARE

A preference space Skyline query processing method based on a Spark environment

The invention discloses a preference space Skyline query processing method based on a Spark environment. The method comprises a space Skyline query processing algorithm based on a preference functionand a space Skyline query processing algorithm based on preference priority. The method is scientific and reasonable;use is safe and convenient, the method comprises the following steps: through the effect of a space Skyline query processing algorithm based on a preference function; the spatial attributes and the non-spatial attributes of the data are integrated, and the data which does not meet the preference of any query point is filtered by utilizing the correlation, so that the size of a data set is reduced, the processing task amount is further reduced by utilizing the grid dominant relationship, and the query processing speed is increased; skyline query processing algorithm based on preference priority is used for clustering spatial data, keywords with high occurrence frequency in the class are used as text feature information of the whole class, and meanwhile, an extended R-tree index is established for spatial objects in the class; efficient space searching and filtering capabilities of the extened R-tree index are dominated and judged, so that Skyline query processing is accelerated.
Owner:NORTHEASTERN UNIV
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