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130 results about "Fixed duration" patented technology

Fixed Duration Basics. Duration generally is used to gauge the long-term implications of completing one project. If you know it will take six weeks for a particular project or set of tasks, you can more effectively plan for other projects before and after that. Effective planning also allows a company to develop and implement long-term strategies by...

Underwater target identification method based on convolutional neural network

The invention discloses an underwater target identification method based on a convolutional neural network, comprising the following steps: firstly, simulating radiation noise of an underwater sound target; secondly, acquiring underwater target tracking beams; thirdly, acquiring a time-frequency graph of each target tracking beam, wherein all the time-frequency graphs are segmented according to fixed duration and divided into training samples and test samples; fourthly, performing data enhancement, size magnification and tailoring on the samples; fifthly, inputting the training samples provided with a label into a built convolutional neural network, performing supervised learning, and obtaining each layer parameter of the convolutional neural network; sixthly, initializing the network by utilizing each layer parameter, and obtaining the convolutional neural network with an underwater target identification function; and seventhly, acquiring radiation noise of a to-be-tested navigation target by a towed array, converting into a time-frequency graph and segmenting, inputting the segmented subgraphs into the convolutional neural network as to-be-tested samples, obtaining an identification result of each subgraph, and taking an identified target with the highest target quantity during identification as a final identification result. The method disclosed by the invention can enable underwater identification to maintain relatively high accuracy and speed under high ocean background noise condition.
Owner:SOUTHEAST UNIV

Video display method

A method for video playback uses only resources universally supported by a browser (“inline playback”) operating in virtually all handheld media devices. In one case, the method first prepares a video sequence for display by a browser by (a) dividing the video sequence into a silent video stream and an audio stream; (b) extracting from the silent video stream a number of still images, the number of still images corresponding to at least one of a desired output frame rate and a desired output resolution; and (c) combining the still images into a composite image. In one embodiment, the composite image having a number of rows, with each row being formed by the still images created from a fixed duration of the silent video stream. Another method plays the still images of the composite image as a video sequence by (a) loading the composite image to be displayed through a viewport defined the size of one of the still images; (b) selecting one of the still images of the composite image; (c) setting the viewport to display the selected still image; and (d) setting a timer for a specified time period based on a frame rate, such that, upon expiration of the specified time period: (i) selecting a next one of the still images to be displayed in the viewport, unless all still images of the composite image have been selected; and (ii) return to step (c) if not all still images have been selected.
Owner:SILVERPUSH PTE LTD

Real-time data statistics method of mass data

The invention relates to a real-time data statistics method of mass data. The real-time data statistics method of the mass data includes the following steps that: (1) a data receiving server transmits data received from a terminal to a data processing server for data processing; (2) the data processing server performs database storage on original signals; (3) the data processing server performs signal statistics and analysis, wherein the step (3) specifically includes: 3.1) distinguishing data types of the signals, and recognizing the data types as a numeric type and a nonnumeric type; 3.2) for the signals of the numeric type, achieving the maximum value, the minimum value and the average value of each signal of the numeric type in fixed duration through statistics, and storing the maximum value, the minimum value and the average value of each signal of the numeric type into a database list of the numeric type; for the signals of the nonnumeric type, achieving appearance times and variation frequency of each state of each signal of the nonnumeric type in the fixed duration, and storing the appearance times and the variation frequency of each state of each signal of the nonnumeric type into a database list of the nonnumeric type. By adopting the real-time data statistics method of the mass data, the volume of original data to be queried is greatly reduced, and the speed of report query and the human-computer interaction experience sense are greatly improved.
Owner:XIAMEN YAXON NETWORKS CO LTD

Carbonate rock thin reservoir porosity prediction method based on seismic even and odd functions

InactiveCN108020863AStrong porosity correlationOvercoming filtering effectsSeismic signal processingPorosityData set
The present invention provides a carbonate rock thin reservoir porosity prediction method based on an seismic even and odd functions. The method comprises the following steps of: the step 101, employing a moving time window with fixed duration to capture short-term seismic signals, and obtaining an even function and an odd function of original signals on a time domain in the moving time window; the step 102, employing a well-logging curve standard and well-side seismic data to obtain a real seismic wavelet to perform standardization of amplitude spectrums of the odd function and an even function, and calculating peak amplitude attributes of the odd function and the even function; and the step 103, allowing the even function peak amplitude attributes and related seismic attribute characteristics to commonly form a multi-attribute data set, and employing multi-attribute analysis to perform fitting of actually measured reservoir porosity data, to obtain a reservoir porosity prediction result in a large scale. The method provided by the invention employs a wavelet standardization method and a method of even function and odd function extraction of seismic data to obtain attributes onlyrelated to the carbonate rock reservoir porosity, and combines a seismic multi-attribute analysis method to perform accurate prediction of the reservoir porosity.
Owner:HOHAI UNIV
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