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64 results about "Window model" patented technology

Windows Driver Model. In computing, the Windows Driver Model (WDM) – also known at one point as the Win32 Driver Model – is a framework for device drivers that was introduced with Windows 98 and Windows 2000 to replace VxD, which was used on older versions of Windows such as Windows 95 and Windows 3.1, as well as the Windows NT Driver Model.

AGV path planning method based on time window optimizing

ActiveCN107179078AReduce calculation complex coefficientsPrecise in and out actionsNavigational calculation instrumentsPosition/course control in two dimensionsTransit systemSpatial planning
The invention relates to an AGV path planning method based on time window optimizing. The AGV path planning method based on time window optimizing comprises the following steps: setting information of key joints, entering joints and exiting joints in a map of a transportation system, and establishing a grid path map in which a transportation line is the same as that of entities of workshops; establishing a storage path of AGV between an entering joint and a target position; detecting feasibility of the path on spatial planning according to the exiting joint and the entering joint, and planning and establishing time window models M of all paths; taking transformation time of the paths as an unique assessment parameter for path optimizing in the time window models M, and selecting the path with the shortest transportation time as an optimal path; and combining a delivery path, the optimal path and the storage path to generate a complete transportation path, establishing a complete path and time window model, successively reading complete path information, and finishing dispatching management of AGV. The time window models are adjusted in time, the working efficiency of the system is greatly improved, a multi-path time window planning method is adopted, and the models are established to solve the collision problem.
Owner:HEFEI UNIV OF TECH +1

Wireless sensor network abnormal event detecting method based on multi-attribute correlation

The invention discloses a wireless sensor network abnormal event detecting method based on multi-attribute correlation and belongs to an anomaly detection technology in data mining.The wireless sensor network abnormal event detecting method comprises the specific steps that non-space-time attribute dependency model is established based on a Bayesian network, the attribute correlation confidence is calculated according to a conditional probability table, the similarity of points to be detected and abnormal points in a non-space-time attribute correlation mode is reflected; time correlation detection is performed based on a sliding window model, readings simultaneously meeting the time correlation mode and abnormal event attribute correlation mode are marked as temporal abnormal points to detect whether abnormal events occur or not by cooperating with neighbor node information.In addition, the wireless sensor network abnormal event detecting method calculates recent abnormal nodes closest to an abnormal event area center by adopting a Ritter's smallest enclosing circle algorithm, uploads the abnormal information of the abnormal nodes and can effectively reduce the data transmission amount and reduce the energy consumption of sensor nodes.The wireless sensor network abnormal event detecting method can be applied to wireless sensor network event detection of multiple sending components.
Owner:JIANGSU UNIV

Stream type repetitive data detection method

ActiveCN102253820AFlexible and Efficient DetectionMaintain stabilityData conversionInternal memoryExtensibility
The invention provides a stream type repetitive data detection method. According to the method, a TBFA (Timing Bloom Filter Array) is constructed for flexibly and efficiently detecting repetitive data in a sliding window model, wherein the TBFA consists of a plurality of TBFs (Timing Bloom Filters) with the same structure, each TBF comprises a bloom filter and a separated timer array used for storing timestamps, the whole TBFA works in a looped first-in first-out mode and gets rid of old elements removed from a data stream monitoring window while recording new elements. The stream type repetitive data detection method is implemented under the sliding widow model, element monitoring is correct to one element, therefore the statistic result based on the stream type repetitive data detectionmethod has good stability; in addition, a part of the timer arrays in the TBFA can be unloaded into a disc, therefore the overhead of an internal memory can be reduced. Theoretical analysis and experimental data show that more than 95% of query efficiency can be maintained when DCBA (Detached Counting Bloom filters Array loads less than 10% of data contents to the internal memory, therefore the method provided by the invention is superior to the traditional technical scheme in space efficiency and expandability.
Owner:HUAZHONG UNIV OF SCI & TECH

GPS (global positioning system) dual-frequency non-difference cycle slip detecting and restoring method and device

InactiveCN104749594AMeet the needs of high-precision positioningImprove the success rate of cycle slip detectionSatellite radio beaconingDual frequencySlide window
The invention discloses a GPS (global positioning system) dual-frequency non-difference cycle slip detecting and restoring method and device. The method includes: reading a GPS observing value, and generating first detection quantity and second detection quantity according to the GPS observing value; utilizing a self-adaptive sliding window model to smooth the first detection quantity, adjusting the first detection quantity after being smoothed according to a first cycle slip judgment threshold value for cycle slip detection to acquire a first detection result; utilizing a epoch difference-solving method for difference solving of the second detection quantity to generate third detection quantity, and performing cycle slip detection on the third detection quantity to acquire a second detection result; analyzing the first detection result and the second detection result, and calculating the first detection quantity and the second detection quantity at a cycle slip epoch to acquire a first cycle slip value and a second cycle slip value; restoring the GPS observing value according to the cycle slip values. By the GPS dual-frequency non-difference cycle slip detecting and restoring method and device, cycle slip detection success rate and cycle slip restoring accuracy can be improved, so that needs on high-accuracy positioning of GPS navigation can be met, and small cycle slip, big cycle slip, special cycle slip and continuous cycle slip can be detected and restored.
Owner:WUHAN UNIV

Simulation experiment device of high-rise building three-dimensional fire behaviors under effect of environment wind

ActiveCN106228890AWind direction is safe and convenientThe wind speed adjustment system is safe and convenientEducational modelsCouplingFlame spread
The invention discloses a simulation experiment device of high-rise building three-dimensional fire behaviors under the effect of environment wind. The device comprises a high-rise building model, a rotary platform, a direction adjustable wind hole, a three-dimensional movable thermoelectric coupling frame and a fire source simulating device. The high-rise building model is a cuboid shell and is divided into four chambers, wherein the ignition experiment chamber is provided with the fire source simulating device and a size adjustable building window model. The bottom of the high-rise building model is connected with the rotary platform and matched with the external direction adjustable wind hole so that environment wind in any direction at any wind speed can be simulated. The three-dimensional movable thermoelectric coupling frame is of a combined rectangular structure, and the parameter measurement function of any position of an external wall surface can be achieved. The simulation experiment device for studying high-rise building three-dimensional fire spreading under the effect of environment wind is established for the first time, a wind direction adjusting system is safe, convenient to use and precise, the experiment device is provided with a complete parameter measuring system, and the complete process of a high-rise building from fire starting, flame spreading to final spreading towards the upper layer and adjacent side of the building can be studied.
Owner:UNIV OF SCI & TECH OF CHINA

Time window online correction-based multi-AGV (Automated Guided Vehicle) path planning method

The invention relates to a time window online correction-based multi-AGV (Automated Guided Vehicle) path planning method. The method includes the following steps that: the operation point sites of anAGV are extracted according to workshop layout information and path information, independent road sections are obtained through division according to the operation point sites; a scheduling system updates an AGV status list and a real-time task list in real time, assigns a task in the real-time task list to an idle AGV, and informs the AGV of a start point and an end point; a feasible path list isestablished, whether a feasible path exists is judged, a task corresponding to the feasible path is added in a time window model, the AGV executes the tasks and feeds back current AGV position information in real time; and whether the current AGV position information is consistent with the position information of the AGV in the time window model is judged, and the time window model is corrected online and updated synchronously. With the time window online correction-based multi-AGV (Automated Guided Vehicle) path planning method of the invention adopted, error accumulation caused by actual errors can be decreased; and a multi-AGV path conflict problem can be solved. The time window online correction-based multi-AGV (Automated Guided Vehicle) path planning is a new dynamic path planning solution suitable for any environment and any number of AGVs, and is suitable for being popularized.
Owner:SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI

Transmission method based on learning energy-efficiency model

The invention discloses a transmission method based on a learning energy-efficiency model. The method comprises the following steps: firstly, periodically recording historical change trends of a network, carrying out weighted smoothing on round-trip delays, and judging change trends of a congestion control window; then establishing models for a network energy efficiency and the congestion control window, when a new ACK (Acknowledgement) is received, updating the energy-efficiency and window models; finally combining with the change trends of the congestion window and the energy efficiency, predicting the size of the congestion control window in a next time period; for a network packet loss or timeout event, using the traditional TCP (Transmission Control Protocol) data packet retransmission mechanism, and when the packet loss is over, reusing the energy-efficiency model for processing. The transmission method disclosed by the invention lowers influences of network random events and estimation errors of the traditional algorithm, and can weigh the delays and particular emphasis of throughputs; in a high-speed network, the higher occupancy rate of a link bandwidth and lower end-to-end delays can be approximated, and the end-to-end delays performed on packet transmission are lowered.
Owner:SICHUAN UNIV

Method, system and apparatus for detecting large-scale complex network community structure

The present invention discloses a method, a system and an apparatus for detecting a large-scale complex network community structure. The method comprises: abstracting a to-be-detected large-scale complex network as atlas data; using a multi-thread parallel sliding window model to carry out optimized storage on the abstracted atlas data; using a multi-thread parallel adaptive tag propagation algorithm to carry out tagged processing on the stored atlas data; and carrying out post-processing according to a tagged processing result and outputting a community structure detection result. The systemcomprises an atlas abstraction module, an optimized storage module, a tagged processing module and a post-processing module. The apparatus comprises a memory and a processor. According to the technical scheme of the present invention, time complexity is reduced and the execution efficiency is improved; the technical scheme of the present invention can also compute the large-scale atlas through anordinary personal computer, so that the cost is reduced; the technical scheme of the present invention can adaptively identify overlapping and non-overlapping communities, so that the community detection accuracy is improved; and the technical scheme of the present invention can be widely applied in the field of complex network service computing.
Owner:GUANGDONG POLYTECHNIC NORMAL UNIV

Passive underwater sound positioning method based on moving time window periodically

The present invention discloses a passive underwater sound positioning method based on moving a time window periodically. The method is composed of a strapdown inertial navigation system (SINS), a single hydrophone (receiver) at the bottom of an autonomous underwater vehicle (AUV) and a seafloor single hydrophone (band sound source), adopts a time window model which moves based on the cycle of an ultrasonic wave sent out by the seafloor hydrophone, and comprises the steps of carrying out the generalized cross correlation on the sound source signals received when the AUV is located at different positions in a time window to obtain the delay inequality, and then calculating a time window internal AUV multi-point model to obtain the latest position coordinate of the AUV. According to the present invention, by calculating the time window internal AUV multi-point model, the AUV does not need to navigate too far, so that a positioning error of an inertial navigation system which accumulates along with the time continuously is reduced effectively. According to the present invention, the AUV does not need to emerge from the water to update the position, does not need the digital communication, and receives an ultrasonic signal passively, so that the position of the AUV is difficult to expose, and the invisibility and the safety of the AUV are improved.
Owner:SOUTHEAST UNIV

Multi-satellite coordinated real-time tracking method for spatial dynamic target

The invention discloses a multi-satellite coordinated real-time tracking method for a spatial dynamic target. The method comprises the steps of firstly establishing a low earth orbit satellite and staring detector model, a tracking task model and a visible time window model; then introducing a rolling time domain concept when real-time tracking is performed on the spatial dynamic target, taking the forward-looking fixed time length T as the rolling time domain to obtain a tracking task of a ballistic missile in the rolling time domain, and establishing a single-layer to-be-tracked task set with the single rolling time domain as a reference, and splitting each to-be-tracked task into a plurality of atomic tasks in the rolling time domain by use of a reverse tree structure to obtain a set ofdetector resources corresponding to each atomic task; and finally, constructing a fitness function based on constraints and objective functions of resource scheduling, and then solving the optimal particle individual based on the fitness value of the particle individual through an evolutionary particle swarm optimization algorithm with crossover and mutation operations, and performing resource scheduling of the detector resources on the single-layer atomic task set according to the optimal particle individual.
Owner:CENT SOUTH UNIV +1

Hyperspectral image abnormity detection method based on constrained sparse representation

The invention belongs to the field of image processing, and relates to a hyperspectral image abnormity detection method based on constrained sparse representation. The method comprises the following steps: (S1), carrying out the linear standardization of a hyperspectral image; (S2), extracting a local background dictionary for each test pixel according to a double-window model; (S3), solving a constrained sparse representation model according to the local background dictionary, and obtaining a first model optimal solution; (S4), deleting all abnormal atoms from the local background dictionaryaccording to the first model optimal solution, and obtaining a new background dictionary; (S5), solving the constrained sparse representation model according to the new background dictionary, and obtaining a second model optimal solution; (S6), calculating a detection value of the pixel according to the second model optimal solution; (S7), traversing the whole hyperspectral image, calculating thedetection values of all pixels of the hyperspectral image, and outputting an image formed by the detection values, i.e., an abnormal detection image. The method does not need the background statistical information and the setting of sparsity, and improves the reconstruction precision.
Owner:NAT UNIV OF DEFENSE TECH
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