909results about How to "Effective prediction" patented technology

A methodology for a daisy-chained memory topology wherein, in addition to the prediction of the timing of receipt of a response from a memory module (DIMM), the memory controller can effectively predict when a command sent by it will be executed by the addressee DIMM. By programming DIMM-specific command delay in the DIMM's command delay unit, the command delay balancing methodology according to the present disclosure “normalizes” or “synchronizes” the execution of the command signal across all DIMMs in the memory channel. With such ability to predict command execution timing, the memory controller can efficiently control power profile of all the DRAM devices (or memory modules) on a daisy-chained memory channel. A separate DIMM-specific response delay unit in the DIMM may also be programmed to provide DIMM-specific delay compensation in the response path, further allowing the memory controller to accurately ascertain the timing of receipt of a response thereat, and, hence, to better manage further processing of the response.

A process and system for integrating information stored in at least two disparate databases. The stored information includes consumer transactional information. According to the process and system, at least one qualitative variable which is common to each database is identified, and then transformed into one or more quantitative variables. The consumer transactional information in each database is then converted into converted information in terms of the quantitative variables. Thereafter, an integrated database is formed for predicting consumer behavior by combining the converted information from the disparate databases.

Adaptive up-sample filtering is used to improve compression efficiency of spatially scalable coding systems by more effectively predicting the high-resolution (enhanced-layer) video (or image) from the low-resolution lower-layer video (or image). Different up-sample filters adaptive to local image properties are selectively used for different portions of a low resolution frame to generate a better up-sampled image. Selection between different up-sample filters is determined by a variety of different information available to both the encoder and decoder. In one embodiment, the up-sample filters are selected by the encoder and then explicitly identified to the decoder. Other techniques are then used to minimize the cost of transmitting the up-sample filter identifiers. In alternative embodiments, the encoder and decoder independently make up-sample filters selections.

The invention provides a method for predicting a dolomite reservoir. The method includes acquiring seismic attributes of a target stratum, increasing the signal-to-noise ratio of the seismic attributes, adopting the seismic attributes with the signal-to-noise ratio increased to perform post-stack wave impedance inversion; adopting the seismic attributes with the signal-to-noise ratio increased to perform pre-stack elastic parameter inversion; adopting the results of the post-stack wave impedance inversion and / or the pre-stack elastic parameter inversion to predict the dolomite reservoir of the target stratum. By an effective predicting method technical system of seismic data quality evaluation, pre-stack depth processing, post-stack attribute analysis and post-stack wave impedance inversion lithologic identification, pre-stack attribute analysis and pre-stack elastic parameter inversion of a high-quality reservoir and hydrocarbon detection of the dolomite reservoir, the dolomite reservoir can be effectively predicted.

A method and an apparatus for elevating compression efficiency of a motion vector by effectively predicting a motion vector of an enhanced layer by means of a motion vector of a base layer in a video coding method employing a multi-layer structure are disclosed. A motion vector compression apparatus includes: a down-sampling module for down-sampling an original frame to have a size of a frame in each layer; a motion vector search module for obtaining a motion vector in which an error or a cost function is minimized with respect to the down-sampled frame; a reference vector generation module for generating a reference motion vector in a predetermined enhanced layer by means of a block of a lower layer corresponding to a predetermined block in the predetermined enhanced layer, and motion vectors in blocks around the block; and a motion difference module for calculating a difference between the obtained motion vector and the reference motion vector.

A system and method are disclosed which predict whether a performance problem within a network is likely to be encountered during future operation. Furthermore, a preferred embodiment not only predicts the likelihood of a performance problem, but further determines the appropriate preventative measures to be taken in an attempt to prevent a predicted performance problem from occurring. In a preferred embodiment, a management system (MS) that oversees the operation of a network is implemented to predict likely performance problems within the network, and may determine appropriate preventative measures for preventing predicted performance problems within the network. Polling gateway(s) may be utilized to periodically poll the network resources in order to retrieve status information for such resources, including but not limited to status of disk(s), database(s), memory, CPU(s), and operating system(s) within the network. The gathered status information is then evaluated by the MS by, for example, correlating such status information with known performance rules for the network to predict potential performance problems, and based on such evaluation, the MS may predict whether a future performance problem is likely to be encountered. Once a future performance problem has been predicted, the MS determines an appropriate preventive action for preventing the performance problem from occurring, and the MS may initiate the appropriate preventive action before the occurrence of the predicted performance problem in an attempt to prevent such performance problem. Most preferably, the network management system is implemented to “learn” symptoms of performance problems over time.

An apparatus and method for improving the compression efficiency of a motion vector by efficiently predicting a motion vector in an enhanced layer from a motion vector in a base layer in a video coding method using a multi-layer structure are provided. The method includes obtaining a motion vector in a mother frame of a base layer that is temporally closest to an unsynchronized frame of a current layer, obtaining a predicted motion vector from the motion vector in the mother frame considering the referencing direction in the mother frame and in the unsynchronized frame and distances between the mother frame and a reference frame and between the unsynchronized frame and a reference frame, generating a residual between the motion vector in the unsynchronized frame and the predicted motion vector, and encoding the motion vector in the mother frame and the residual.

The invention proposes a method for synchronously recognizing identities and expressions of human faces. The method comprises the steps of extracting facial features of each human-face image, defining corresponding semantic features for each image and adopting a feature fusion method of kernel principal component analysis (PCCA) for the facial features so as to enable input image features to have better recognition properties. On the basis, a model of the relation between the facial features and the semantic features is established by use of a partial least-squares regression (PLSR) method, and expression-identity recognition is performed on to-be-recognized human-face images by use of the model. Experiments show that the method proposed by the invention not only can synchronously recognize human faces and expressions, but also can improve the recognition rate of human-face expression recognition.

An apparatus comprising (i) a segmentor circuit, (ii) a plurality of encoders and (iii) a multiplexer circuit. The segmentor circuit may be configured to segment a picture into a plurality of strips. Each of the plurality of encoders may be configured (i) to encode respective strips of the plurality of strips in parallel and (ii) to transfer context information with at least one other encoder of the plurality of encoders. The multiplexer circuit may be configured to combine the encoded strips from the plurality of encoders into an encoded bit stream.

The invention discloses a prediction and evaluation technology of 3D seismic optimum time window river channel sand body reservoirs, belongs to the technical field of the prediction and evaluation of the 3D seismic reservoirs, and aims at solving technical problem that the river channel predictive resolution of the traditional methods is not enough. The technical proposal is as follows: the 3D visualization scanning is performed on each reservoir at the interval of 1-2ms, the optimum time window is determined according to the scope shown by the target river channel, the corresponding subfield is cut out, clairvoyance and scanning are carried out on the time window properties, such as root-mean-square amplitude, wave impedance and the like, auto-tracing is performed, top surface and bottom surface are picked up, a time isopach map is calculated and converted into a sand body isopach map, a top surface structure diagram is formed by time-depth conversion, and the reservoir physical properties are evaluated by curve reconstruction, thus realizing the prediction and evaluation of the plane morphology, longitudinal thickness and the reservoir physical properties of the river channel sand body. The method adopts the optimum time window to effectively inhibit interference, is applicable to various data volumes, and can effectively predict and evaluate a thin river channel sand body with the thickness far less than 1 / 4 of a wavelength under the condition of frequent interbedding of sand and mudstone, the thin river channel sand body comprises the river channel sand body which is not corresponding to wave crest or wave trough, and the method has good application effect in petroleum exploration and development.

The invention discloses a multi-target tracking method based on multi-model fusion and data association; the tracking method comprises the following steps: firstly using an interframe difference method to detect a motion target contour and center of mass coordinates; fusing a pyramid optical flow method with Kalman filtering so as to predict the center of mass coordinates of the motion target in the next moment; using Euclidean distances between the center of mass coordinate predicted value and the center of mass coordinate detection value at next moment to form a benefit matrix, and using a Hungary algorithm to obtain the optimal matching through data association; finally removing certain portion unable to satisfy requirements in a tracker, and building a tracking unit for non-assigned detections, thus realizing multi-target tracking. The tracking method can be less affected by light changes and background noise interferences, thus solving the tracking failures caused by target blocking or mutual interferences between targets, providing multi-target tracking accuracy, and providing well instantaneity and robustness.

The invention relates to a quick chemical leakage predicating and warning emergency response decision-making method which combines diffusion model simulation with a neural network and a gas sensor system and is applied to quick warning and aid decision making of leakage of harmful gas in an industrial park. The method includes park risk factor identification, numerical simulation, data screening, neural network training and sensor system and neural network model integration, wherein the park risk factor identification is used for identifying various possible leakage accidents, the numerical simulation includes simulating all the possible accidents to obtain a range of influences of the harmful gas, the data screening includes extracting and reconstructing an effective part in a numerical simulation result according to actual sensor layout, the neural network training includes training specific neural network models by the aid of screened data so as to acquire model parameters aiming for the specific industrial park and surrounding conditions and using redundant data for parameter validation, and sensor system and neural network model integration includes combining the models with a sensor DCS (distributed control system).

Provided is a method that determines a reference picture index and a motion vector of a current prediction unit, derives spatial motion vector candidates using valid motion vectors of neighboring prediction units each of which exists at a predetermined position, derives temporal motion vector candidate of the current prediction unit, determines one of the spatial and temporal motions vector candidates as a motion vector predictor, calculates a motion vector difference between the motion vector of the current prediction unit and the motion vector predictor and encodes the motion vector difference and the reference picture index.Therefore, a motion vector is effectively predicted not only when motion of image is ordinary but also when the motion of image is little or steady or the image to be encoded is a background image.

A method, apparatus, system and computer program product are provided for determining one or more current or future conditions regarding capacity and allocation of resources in an institution. The apparatus enables personnel to utilize predictive tools to identify in real-time or in the near future areas of capacity constraints within the institution. The apparatus includes a processor configured to analyze data which includes information associated with the institution. A portion of the data is generated in real-time during an actual time in which events occur. The processor is capable of using at least a portion of the data to identify current conditions or generate one or more predictions regarding conditions to occur in the future that are associated with resources and capacity of the institution. Also, the processor is capable of analyzing results of the predictions and allocating resources of the institution on the basis of the predicted results.

The invention relates to a coupling simulation method of a flow and sediment process of a distributed watershed. The method comprises the steps of digital terrain processing, building of a contour strip, building of a contour strip erosion landform data file, data collecting and processing, watershed hydrological process computation, slope erosion and sediment transport process computation, flow and sediment process computation of a channel or a river or a reservoir, judgment, variable parameter transferring, model parameter calibration and model validation, and ending. According to the coupling simulation method, the contour strip is taken as a computing platform for the slope scale, and the real flow and sediment physical process of a slope is taken as a picture, so that the coupling simulation computing capability for rainfall-runoff and erosion-sediment processes of the contour strip slope is achieved; the computational accuracy is ensured on the premise of reducing the computing amount; and the flow and sediment process of the slope with any grid scale is effectively reduced and predicted. Compared with the prior art, the coupling simulation method has the advantages that the terrain adaptability and the scale adaptability are achieved by taking the contour strip as a basic computing unit; meanwhile, deeper recognition of the law of the flow and sediment process of the slope can be achieved on the basis of physical flow and sediment process simulation of the slope and a more complicated practical application is supported.

The invention relates to a numerical control machine tool thermal error real-time compensation modeling method based on a time series algorithm, which belongs to the technical field of precision machining. The method comprises the steps of (1) carrying out data zero mean pretreatment, namely employing an inverted sequence test method and a kurtosis and skewness test method to judge the stationarity and the normality of the data; (2) using an autocorrelation function, a partial correlation function, and the censored results as judgment criteria to carry out the pattern recognition of a thermal error mathematical model; (3) employing a least square estimation method or a long autoregressive residual calculating method to realize the parameter estimation of the thermal error mathematical model; (4) determining the order of the thermal error mathematical model, namely employing a judgment method that combines an AIC order determination criterion, an F test order determination criterion, and a whiteness test order determination criterion to realize the order determination of the thermal error mathematical model; (5) and carrying out integration processing of synthesizing judgment conditions, namely constructing a complete forecasting mathematical model formula. The modeling method provided by the invention has the advantages that less hardware is required, the applicability is wide, and the established model has high prediction precision and reliability.

The invention discloses a high-temperature creep deformation prediction and creep damage analysis method for a high-chrome steel component. The method comprises the following steps of: establishing a theoretical model, determining material parameters, designing a numerical integration algorithm, carrying out the secondary development of finite element software, carrying out the creep damage analysis of the component and the like. Compared with an existing technical scheme, the method disclosed by the invention is characterized in that a great improvement is carried out, the accurate prediction of the creep behavior and the creep damage of the high-chrome steel component can be realized, and therefore, the method has an important application value in the fields of the security design and the residual life evaluation of high-temperature high-pressure components in a supercritical generator set.

A methodology for reservoir understanding that performs investigation of asphaltene instability as a function of location in a reservoir of interest. In the preferred embodiment, results derived as part of the investigation of asphaltene instability are used as a workflow decision point for selectively performing additional analysis of reservoir fluids. The additional analysis of reservoir fluids can verify the presence of asphaltene flocculation onset conditions and / or determine the presence and location of phase-separated bitumen in the reservoir of interest.

Systems, processors, and methods for determining when to enter loop buffer mode early for loops in an instruction stream. A processor waits until a branch history register has saturated before entering loop buffer mode for a loop if the processor has not yet determined the loop has an unpredictable exit. However, if the loop has an unpredictable exit, then the loop is allowed to enter loop buffer mode early. While in loop buffer mode, the loop is dispatched from a loop buffer, and the front-end of the processor is powered down until the loop terminates.

A learning-based visual attention prediction method is disclosed. The method includes a correlation relationship between the fixation density and at least one feature information being learned by training, followed by a test video sequence of test frames being received. Afterward, at least one tested feature map is generated for each test frame based on the feature information. Finally, the tested feature map is mapped into a saliency map, which indicates the fixation strength of the corresponding test frame, according to the correlation relationship.

A system and method for shallow water simulation may provide a framework for solving General Shallow Wave Equations (GSWE) to efficiently simulate 3D fluid effects on arbitrary surfaces using a height field representation. The height field representation may include height columns constructed along surface normals, which may be dependent on a condition of boundary cells adjacent to fluid cells and / or artificial viscosity effects. The framework may provide implicit schemes for solving for the effects of external forces applied to the fluid, including gravity and surface tension, and explicit schemes for solving for advection effects. The system and method may be implemented on general-purpose CPU(s) and / or GPU(s) and may be capable of simulating a variety of fluid effects including: waves, rivulets and streams, drops, and capillary events. In some embodiments, the system and method may achieve real-time fluid control and fluid shape design through user-interaction (e.g., in a graphical painting application).

A system and method for efficient predicting and processing of memory access dependencies. A computing system includes control logic that marks a detected load instruction as a first type responsive to predicting the load instruction has high locality and is a candidate for store-to-load (STL) data forwarding. The control logic marks the detected load instruction as a second type responsive to predicting the load instruction has low locality and is not a candidate for STL data forwarding. The control logic processes a load instruction marked as the first type as if the load instruction is dependent on an older store operation. The control logic processes a load instruction marked as the second type as if the load instruction is independent on any older store operation.

The invention relates to a ship conflict early warning method. The ship conflict early warning method comprises the following steps that the real-time position information and the historical position information of a ship are obtained through maritime radar and are processed primarily; ship trajectory data are preprocessed at each sampling moment, clustering is conducted on the ship trajectory data at each sampling moment, parameter training is conducted on the ship trajectory data at each sampling moment by means of a hidden Markov model, the hidden state q corresponding to an observation value at the current moment is obtained at each sampling moment according to parameters of the hidden Markov model by means of the Viterbi algorithm, a predicted value of the position of the ship in the future time period is obtained at each sampling moment through a set prediction time domain W based on the hidden state q at the current moment, the dynamic behaviors of the ship are monitored in real time by establishing a safety rule set, and a warning message is sent out in time. According to the ship conflict early warning method, the trajectory of the ship is predicted in real time in a rolling mode, effective early warning of maritime conflicts is achieved, and the safety of marine traffic is improved.

The invention discloses a particle filtering-based pupil tracking method in a sight tracking system and belongs to the field of human-computer interaction. Aiming at a problem that the pupil tracking efficiency in the conventional infrared image is poor, the method creates a concept of a tri-channel pseudo color image (TCPCM) which fully uses information of each channel, enables the characteristics of a pupil to be obvious, and improves the stability and the accuracy of tracking. Aiming at a problem that a background interferes in a pupil tracking process, the method creates a pupil object model which accords with the morphological characteristics and change rules of the pupil to fully differentiate the front background from the back background so as to decrease the interference of the background to the object model. Aiming at a problem that the prediction effect of the position and the form of the pupil is poor, the method creates a state transition equation embodying the motion rules of the pupil, fully considers various conditions of the state change of the pupil and can effectively predict the position and shape of the pupil. Through high-quality characteristic detection and tracking, the method enables the precision of a developed sight tracking system to reach a level of real-time human-computer interaction.

An approach is provided for generating a high dynamic range image from a low dynamic range image. The generation is performed using a mapping relating input data in the form of input sets of image spatial positions and a combination of color coordinates of low dynamic range pixel values associated with the image spatial positions to output data in the form of high dynamic range pixel values. The mapping is generated from a reference low dynamic range image and a corresponding reference high dynamic range image. Thus, a mapping from the low dynamic range image to a high dynamic range image is generated on the basis of corresponding reference images. The approach may be used for prediction of high dynamic range images from low dynamic range images in an encoder and decoder. A residual image may be generated and used to provide improved high dynamic range image quality.

A method and apparatus are provided for improving the compression efficiency of motion vectors of an unsynchronized picture by efficiently predicting the motion vectors using motion vectors of a lower layer. The method compresses motion vectors of an unsynchronized picture belonging to a current layer in a video encoder based on a multilayer having at least the current layer and a lower layer of the current layer. The method includes selecting a base picture for the unsynchronized picture, generating a predicted motion vector of the current layer from a motion vector of the base picture, subtracting the predicted motion vector from a motion vector of the unsynchronized picture, and encoding the result of subtraction.

The invention discloses a patent hotspot discovery and trend analysis method. During the discovery process of patent hotspots, firstly, word classification is carried out, similarity among patent documents is calculated, and the patent documents are classified according to the similarity; then phrases of each cluster are combined so that results are more concise and visual; then hotspot techniques are discovered through the hotspot calculation method, and the hotpot degree of each hotspot technique is analyzed; and lastly, curve fitting is carried out according to historical data, a current technical life cycle of one technique is judged by means of a logistic regression curve, and development conditions and potential research value of the technique are further analyzed. Meanwhile, effective trend analysis is carried out on the hotspot techniques, and a development trend of each technique is presented. According to the patent hotspot discovery and trend analysis method, effective information can be discovered from a large amount of precious patent data, and wide practicality and high market value are achieved.