672 results about "Adaptive selection" patented technology

A method of adaptively selecting an optimum data deduplication chunking method receives a request to deduplicate a file, wherein the file has a file type. The method searches a table of file types, wherein the table includes, for each file type, a chunking method, a deduplication ratio, and a depulication ratio threshold. The method selects a chunking method for the file according to the table. The method chunks the file using the selected chunking method. The method deduplicates the chunked file according to prior art deduplication methods. The method calculates a deduplication ratio for the file type and updates the table with the calculated deduplication ratio for the file type. If the calculated deduplication ratio for the file type is less than the deduplication ratio threshold for the file type, the method selects a new chunking method for the file type and updates the table of file types with the new chunking method for the file type.

Techniques used to enhance the execution of long-running or complex software application instances and jobs on computing systems are disclosed herein. In one embodiment, a real time, self-predicting job resource monitor is employed to predict inadequate system resources on the computing system and failure of a job execution on the computing system. This monitor may not only determine if inadequate resources exist prior to execution of the job, but may also detect in real time if inadequate resources will be encountered during the execution of the job for cases where resource availability has unexpectedly decreased. If a resource deficiency is predicted on the executing computer system, the system may pause the job and automatically take corrective action or alert a user. The job may resume after the resource deficiency is met. Additional embodiments also integrate this resource monitoring capability with the adaptive selection of a computer system or application execution environment based on resource capability predictions and benchmarks.

Autonomous selection between multiple virtualization techniques implemented in a virtualization layer of a virtualized computer system. The virtual machine monitor implements multiple virtualization support processors that each provide for the comprehensive handling of potential virtualization exceptions. A virtual machine monitor resident virtualization selection control is operable to select between use of first and second virtualization support processors dependent on identifying a predetermined pattern of temporally local privilege dependent instructions within a portion of an instruction stream as encountered in the execution of a guest operating system.

A self-adapting method which is used for a relay strategy of a multiple-relay cooperative communication respectively selects an appropriate retransmission mode and distributes a corresponding transmission power for each relay code according to the state of current real-time channel. Or a direct transmission mode is decided to be selected in order to realize the maximization of the channel capacity of the system and provide a high-efficiency communication under the state of reliability. The method mainly comprises the following operation procedures: (1) estimating the channel, (2) selecting a cooperative partner, (3) choosing an optimum relay strategy for each rely with the result of channel estimation and partner selection, (4) respectively calculating the capacity of the direct transmission channel and the capacity of the channel of the selected relay plan according to the formula of channel capacity, and (5) taking the plan with larger capacity of the equivalent channel as a final selection result. The method determines whether the relay is used according to the current channel state, and selects an optimum retransmission strategy for each relay under the precondition that the reliability and availability of the communication are considered and reasonably distribute power between the signal source and each relay.

The invention belongs to the technical field of radar remote sensing, and relates to an attention pyramid network-based SAR image multi-scale ship detection method. On the basis of an existing featurepyramid network, the invention provides a multi-scale feature extraction method with adaptive selection of significant features, namely the feature pyramid network based on a dense attention mechanism, and the method is applied to SAR image multi-scale ship target detection. Prominent features are highlighted from global and local ranges through the channel attention model and the spatial attention model respectively, and better detection performance is obtained; meanwhile, the attention mechanism is applied to the multi-scale fusion process of each layer, the characteristics can be enhancedlayer by layer, false alarm targets can be effectively eliminated, and the detection precision is improved.

A method selects antennas in an OFDMA network. A channel state of a downlink is measured using a downlink subframe received in a mobile station from a base station. A channel state of an uplink is measured using an uplink subframe received in the base station from the mobile station. Next, the method compares the channel states to determine whether the downlink and the uplink are reciprocal or not. The mobile station can perform receive antenna selection based on the quality of the downlink channel state. The mobile station can also perform transmit antenna selection when instructed by the base station.

The invention discloses a distribution network single-phase ground fault route selection method based on a transitional quantity signal. The method comprises the following steps: determining the initial time of the fault; the adaptive selection of the characteristic frequency-band; and calculating and comparing the transient zero-sequence current-component amplitude value in the characteristic frequency-band; the invention definitely distinguish the fault line and the healthy line by using the characteristic that the abundant transient high-frequency component is include in the fault current at the moment of occurrence of the single-phase ground fault; and the method can adaptively determine the characteristic frequency-band and perform fault route selection by using the characteristic quantity of the transient zero-sequence current in the characteristic frequency-band, and the success ratio reaches above 99 percent through a great mount of simulation and the field data test, and is far higher than that of the route selection method in the prior art at present. The route selection method can be applied to the fault route selection for the transformer station where the neutral point is not grounded and is not directly grounded.

The invention relates to a self-adaptive screening method for an anticipated fault set in power system security and stability on-line assessment, which is suitable for determining the anticipated fault set in the static, transient and dynamic security and stability on-line assessment of the power system. The method adopts the core concept that the fault set required to be recalculated in the security and stability on-line assessment is determined according to the mode of the security and stability margin of all anticipated faults given by the security and stability on-line assessment in the previous round of the power network. The invention takes the power network security and stability margin and the security and stability mode as the quantitative index of the power network security and stability degree, takes the security and stability margin as the index, and screens the anticipated fault subset required to be recalculated from the anticipated fault universal set by combining the security and stability mode and the degree of change of the running state of the power network as the dynamic anticipated fault set which meets the practical demands of the engineering and is changed along with the running state of the power network; the scale of the anticipated fault set used for the security and stability on-line assessment under the current time section can be reduced, and the computing speed for the security and stability on-line assessment is increased.

The present invention discloses a system and method for adaptive selection of scanning modes based on the content of the input image sequence. In one embodiment, two encoders are employed. A first encoder receives the input image sequence and encodes each frame of the image sequence using at least two different scanning modes, e.g., zigzag scanning mode or alternative scanning mode in accordance with the MPEG-2 standard or the like. Specifically, different portions of each frame will be scanned using different scanning modes. This first encoding provides look-ahead information so that a second encoder is able to assign DCT quantized coefficients in a more efficient scanning order, thereby reducing encoding bits and/or improving the picture quality.

A self-adaptive selection dynamic production scheduling control system, which is realized via a computer, is characterized in that: the system comprises a system emulator, a learning machine, a decision-making machine, a scheduling rules base, a scheduling knowledge base, a carrier, processing equipments and a buffer station thereof; the buffer station is provided with an optical grating, a sensor and a detection equipment; when a working piece reaches the buffer station and is processed, the learning machine detects the current system status for learning, so as to acquire dynamic scheduling knowledge about the system and update the knowledge in the scheduling knowledge base; when one processing equipment needs to be scheduled, the decision-making machine reads corresponding scheduling knowledge in the scheduling knowledge base according to the detected system status, acquires new scheduling knowledge through continuous interactive learning with the processing system, dynamically selects the scheduling rules based on the status of the processing equipments and the working piece in the system, and chooses the optimized scheduling rules to schedule the processing equipments. The invention can adapt to instable time-varying workshop dynamic production environments, obtain a better working-piece arrangement than prior rule-based scheduling technology, effectively reduce the process waiting time, and improve the fill rate of product delivery time.

The invention discloses a forward-looking self-adaptive speed control method of high-speed numerical control equipment. The numerical control system of the method conducts a plurality of layers of pre-reading decoding processing, uses pre-reading program segment information for pre-calculation to the terminal speed of a segment to be processed, adjusts a speed acceleration and deceleration time constant according to the calculation result, selects a speed acceleration and deceleration curve type, and then conducts a fast speed acceleration and deceleration calculation to an S curve so as to lead the numerical control equipment to process the micro-segments with high speed and smooth operation. The forward-looking self-adaptive speed control method comprises the following steps of: the pre-calculation of the terminal speed of the segment to be processed, the self-adaptive selecting strategy of the speed acceleration and deceleration time constant, and the speed acceleration and deceleration curve type; and the fast speed acceleration and deceleration calculation of the S curve. The invention provides a self-adaptive speed acceleration and deceleration control method for the high-speed numerical control equipment, leads the numerical control equipment to have the capacity of processing the micro-segments with high speed and smooth operation, and satisfies the speed control requirements of high-speed high-precision numerical control equipment.

An integrated radiation detector having a pulse-mode operating photosensor optically coupled to a gamma sensing element and a neutron sensing element is disclosed. The detector includes pulse shape and processing electronics package that uses an analog to digital converter (ADC) and a charge to digital converter (QDC) to determine scintillation decay times and classify radiation interactions by radiation type. The pulse shape and processing electronics package determines a maximum gamma energy from the spectrum associated with gamma rays detected by the gamma sensing element to adaptively select a gamma threshold for the neutron sensing element. A light pulse attributed to the neutron sensing element is a valid neutron event when the amplitude of the light pulse is above the gamma threshold.

A method for self-adapting selection network, first through the terminal equipment gets all adaptable network; then judges it whether or not can start self-adapting, so takes the bootable self-adapting network to record according to the priority sequence of self-adapting network mode, then starts the self-adapting, the terminal equipment compares the top priority wireless network with the current use networks, if they are the same, then no switching, otherwise switch it to the top priority wirelesss networks; repeats the said steps until find optimum network condition.

The invention discloses a digital image noise reduction method and device. The noise reduction method includes: performing noise analysis on an input image, calculating the difference frame/field image between input image frames or between two fields separated by one field, and based on the difference frame Image analysis of the frame/field noise statistical characteristics; perform noise analysis, calculate noise power, determine noise signs and determine noise classification; adaptively select frame/intra-field noise reduction or/and frame/inter-field noise reduction methods. The device for digital image noise reduction includes: frame memory, noise analysis unit and frame/field noise reduction unit. Since the present invention selects and adopts frame/intra-field and/or frame/inter-field noise reduction methods by analyzing the noise characteristics of difference frame/field images, and selects appropriate weights according to the characteristics of noise and image information, the noise reduction Finally, images with better visual effects are obtained.

Several implementations relate, for example, to depth encoding and/or filtering for 3D video (3DV) coding formats. A sparse dyadic mode (308) for partitioning macroblocks (MBs) along edges in a depth map is provided as well as techniques for trilateral (or bilateral) filtering of depth maps that may include adaptive selection between filters sensitive to changes in video intensity and/or changes in depth. One implementation partitions a depth picture, and then refines the partitions based on a corresponding image picture. Another implementation filters a portion of a depth picture based on values for a range of pixels in the portion. For a given pixel in the portion that is being filtered, the filter weights a value of a particular pixel in the range by a weight that is based on one or more of location distance, depth difference, and image difference.

A method for inserting adaptive pilot frequency in OFDM system includes using the sending end to adaptively select pilot frequency model with different interval according to channel parameter estimated by receiving end; increasing pilot frequency interval and applying pilot frequency model lowering pilot frequency quantity when channel is changed at low speed; reducing pilot frequency interval and applying pilot frequency model increasing pilot frequency quantity when channel is changed at high speed; dividing channel parameters, maximum delay expansion and relative Doppler frequency shift to be sections and using different pilot frequency interval to correspond to different pilot frequency model.

The invention provides a fast partitioning method of HEVC (High Efficiency Video Coding) intraframe coding units based on a decision tree. The method comprises the following steps: acquiring texture features of a current coding unit by constructing a histogram, wherein the texture features comprise the number of edge points of the current coding unit, the variance of a brightness value, the variance of a mean value of a subblock brightness value of the current coding unit and the variance of a subblock brightness value variance; and predicting the coding depth of the current coding unit by adopting a decision tree model according to the texture features. Since the texture features of the current coding unit are analyzed by constructing the histogram, and adaptive selection of the coding scale is performed by using the texture features through the decision tree model, thus unnecessary coding scale calculation can be skipped; and besides, experimental results show that the method provided by the invention saves 31% coding time on average during intraframe coding, while the average bit stream is increases by about 2.6% and at the same time, the PSNR of a video basically remains unchanged, thereby greatly reducing the coding complexity of the HEVC.

The color coding approach adopted by the Anchor Point Cloud Compression (PCC) leads to a significant color distortion, even at very low compression ratios. This color distortion is also referred to as color leaking Two approaches are able to mitigate the color leaking Both approaches reduce the color leaking significantly, while one of them (e.g., 1D subsampling) is more robust and preferred in most cases. A more general approach is an adaptive selection between these two approaches.

An information system of vessel on inland river comprises a system general control centre with CTI system server, multiple system branch control centers with CTI system server and vessel mobile terminals. It features that multiparty all duplex communication can be applied by whole system when rescue is carried out for distress vessel, double way of data transmission between mobile terminal on vessel and control centre can be carried out by the system, public network communication mode can be adapted by the system and simultaneously positioning system can be selected adaptively.

The invention discloses a remote sensing image ground object classification method based on superpixel coding and convolution neural network, using adaptive superpixel coding and double channel convolution neural network. The remote sensing image ground object classification method based on superpixel coding and convolution neural network includes the steps: utilizing a superpixel algorithm to perform image pre-segmentation; using a cluster method to merge neighboring and similar superpixel blocks, setting the size of the taken blocks, constructing three double channel convolution neural networks with different input size; inputting samples with different taken block size into the corresponding network; using the convolution neural networks to extract the data characteristics of two sensors respectively; merging the extracted characteristics for classification; and according to the size of the merged pixel block, determining the size of the taken blocks of the samples, and realizing adaptive selection of the utilized neighborhood information. The remote sensing image ground object classification method based on superpixel coding and convolution neural network can realize adaptive selection of the utilized neighborhood information to enable the neighborhood information to realize positive feedback effect and preferably utilize the neighborhood information to send the samples to different networks according to the neighborhood information so as to enable the samples with similar distribution to enter the same network, thus effectively improving the classification accuracy.