65 results about "Assignment function" patented technology

A system for efficiently distributing messages to a server farm uses a hashing function and a map-based function, or combinations thereof, to distribute messages associated with a processing request. In one implementation, for example, the hashing function has inputs of an identifier for each message in a processing request, and a list of available servers. Upon identifying that any of the servers is unavailable, or will soon be unavailable, the load balancing server uses an alternate map-based assignment function for new requests, and inputs each assignment into a server map. The load balancing server can then use the map or the hashing function, as appropriate, to direct messages to an operating server. Upon receiving an updated list of available servers, the load balancing server can switch back to the hashing function after the map is depleted, and use the updated server list as an argument.

Some embodiments of the present invention provide blade servers having blade switches that function as switches in the data plane, but do not have a Domain_ID. Control plane switching functions are performed by a fabric switch (e.g., a core switch) to which the blade server is attached. A fabric switch to which a blade switch is attached may perform address assignment functions for blades of the blade server. The blade switch preferably converts FLOGI requests to FDISC requests that are forwarded to an attached fabric switch. Some implementations provide for the multiple fabric switches, all of which are configured for communication with at least one blade switch, to establish and maintain the state of a virtual Domain_ID.

The invention concerns methods for the wavelength calibration of spectrometers and in particular secondary spectrometers which achieve considerably better calibration accuracies than the conventional peak search methods especially for spectrometers with a relatively large bandwidth. The methods according to the invention are based on the principle of a stepwise relative shift of corresponding measured-value blocks of a model and calibration spectrum where a correlation value is calculated for each shift step. A shift value is determined for each measured-value block at which the correlation value reaches an optimum. A value pair consisting of a position marker of the measured-value block and the associated shift value is determined for each measured-value block. These value pairs represent the design points for fitting to a suitable assignment function. The coefficients obtained in this manner can be used directly as coefficients of a wavelength assignment or be combined with the coefficients of an existing first wavelength assignment in that they for example replace these coefficients or are offset against the coefficients of an existing first wavelength assignment.

Systems and methods are disclosed for an optimizing operations at a contact center. In one embodiment, an integrated contact center comprises: a workforce manager comprising a scheduler and a tracking function; and a lesson assignment function configured to receive at least one indicator of performance of the agent, and further configured to assign a lesson to the agent based on the at least one indicator.

The invention discloses a remote sensing image change detection method based on multi-feature proof integration and structure similarity, comprising the following steps: A. data preparation: selecting remote sensing images to be carried out with change detection in different time phase and in the same spatial scope; B. feature extraction: respectively extracting features of textures, grads and edges of images in two time phases; C. structure similarity calculation: calculating the texture structure similarity, grads structure similarity and edge structure similarity of the remote sensing images in two time phases in a working window; D. basic probability assignment function determination: building basic probability assignment function (BPAF) of evidence theory based on texture structure similarity, the grads structure similarity and edge structure similarity; and E. forming evidence and obtaining change areas to realize change detection. The method carries out change detection based on the area statistic features of edges, texture sand grads of images and can effectively avoid detection miss and false detection caused by the change detection using single feature; and the algorithm has robustness.

The invention discloses a D-S-evidence-theory-based distribution automation terminal state diagnosis method. The method comprises: statistics of designated state characteristic quantities is carried out from operating information uploaded to a main distribution station from a distribution automation terminal; distribution automation terminal states are graded and a fuzzy membership function, corresponding to different distribution automation terminal states, of the state characteristic quantities is constructed; various membership parameters of the fuzzy membership function are determined; with the distribution automation terminal state grading result as a single element proposition, a basic probability assignment function and an evidence fusion result are calculated for the single element proposition and an identification frame; and matching is carried out on the evidence fusion result and a preset terminal state diagnosis decision-making criterion, so that a current state of the distribution automation terminal is obtained. According to the invention, the state of the distribution automation terminal can be determined accurately based on the operating information; the detection result is accurate and reliable; the diagnosis becomes convenient and rapid; and the operability is high.

When a user logs in to an MFP (S200), places an original on a scanner, and instructs the MFP to start a process, the MFP scans the original to recognize characters and words, and creates a word appearance frequency list (S201). Thereafter, records (histories) contained in information about histories of jobs that were executed in the past are narrowed into histories that were executed by users having the same attribute as that of the login user (S202). Functions of jobs contained in identified histories are compared, and job histories having similar functions are grouped. Finally, functions and settings of remaining histories are displayed on a user interface (S204). When any of them is selected, a document is processed according to the selected function and setting (S205). Thereafter, a history of the job is stored (S206).

The invention discloses an evidence theory-based multi-source information fusion risk analysis method, which belongs to the technical field of information processing. The method comprises the following steps of: determining an index and a weight of a risk system by using an analytic hierarchy process; dividing a risk level by using a mean principle in a statistical method and generating basic probability assignment; fusing basic probability assignment by a weighted fusion method which effectively processes conflicting evidence; determining a main focal element of a fusion result; and obtaining the risk level of the risk system according to the corresponding relationship between the risk level and a basic probability assignment function focal element so as to realize risk analysis. The method has high generality and the advantages of low calculation complexity and high instantaneity and can be conveniently applied to risk evaluation of the system.

The invention provides an automatic test system for wavelength-selective switch, which comprises a light source generating device, a tested WSS module and a spectrum recording device connected with each other through an optical physical channel and a system control device respectively connected with the three parts. The system control device controls the light source generating device to generate the sequence signal with fixed wavelength needed for the test and controls various ports of the measured WSS module to form the fixed assignment relationship aiming at the wavelength sequence signal; the spectrum recording device records and returns the spectrum information output by various ports of the tested WSS model; and the system control device matches the returned spectrum information with the expected result to decide whether the assignment function of the tested WSS module is normal and position the tested WSS module and the ports of the tested WSS module with abnormal assignment function. The invention can realize the automation and batching of the test process, thus leading to the sharply reduced error rate and enhanced test efficiency.

The invention relates to a target detection method and system based on spatial-temporal information fusion, belonging to the technical field of signal processing. According to the scheme of the invention, before fusing output evidences, each output evidence is first screened, the evidences with poor classification effect or poor evidence correlation are eliminated according to the correlation among the output evidences, so that the invalid or unsatisfactory classification results can be prevented from entering a fusion process, the support level of the output evidences for a correct target canbe enhanced, and the support level for other targets can be relatively reduced. According to the scheme of the invention, on the one hand, the amount of calculation can be reduced, and the efficiencycan be improved; and on the other hand, the convergence of fusion results towards assumption sets can be accelerated, the influence on the output evidences of a target to be recognized caused by theunsatisfactory individual basic probability assignment functions can be reduced, the risk of misjudgment or missed judgment can be reduced, and the recognition accuracy can be improved.

The invention relates to a mechanical product fault mode identification method based on an evidential neural network model. The mechanical product fault mode identification method defines a novel evidential neural network model based on an evidence theory and a radial basis function neural network model, performs mode determination on signal features of a mechanical product based on the evidentialneural network model for identifying fault modes, gives consideration to the features of limited sample amounts and high precision requirement, is based on the evidence theory and the neural networkmodel, utilizes a basic belief assignment function of the evidence theory to evaluate uncertainty in the neural network training process, utilizes an evidence fusion method for carrying out information fusion, and can improve the precision of fault mode identification by means of an evidential neural network.

The invention provides a reservoir adaptive scheduling method based on the D-S evidence theory, which is characterized by including the following steps: S1, predicting the temperature and precipitation within a future research time through GCMs (Global Cycle Model) and a downscaling technology, taking the prediction result as the input predicted runoff of a hydrological model, and taking the runoff prediction results output by GCMs as multiple future climate change scenarios; S2, constituting a recognition framework with each potential climate change scenario as a focal element Theta in the D-S evidence theory; S3, defining corresponding basic probability assignment functions m1, m2 and m3; S4, synthesizing three evidences based on a modified D-S synthesis rule, and calculating the synthesis probability m123 of the scenarios; S5, letting the weight Alpha of each scenario be equal to a trust function; and S6, constructing a reservoir optimal scheduling model with the maximum weighted average of the average benefits over the years as an optimization objective, setting a linear scheduling function, and optimizing the parameters of the scheduling function through a simulated optimization approach to get an adaptive scheduling scheme.

The invention discloses a full diversity multi-antenna two-way relay receiving method based on combination of a Dempster-Shafer evidence theory and a physical-layer network coding. Firstly, a multi-antenna two-way relay model without direct link is built; then, performance and defects of the prior multi-antenna two-way relay receiving algorithm based on a decode-and-forward network coding and the physical-layer network coding are analyzed, moreover, according to the defects of the prior algorithm, the full diversity multi-antenna two-way relay receiving method based on combination of the Dempster-Shafer evidence theory and the physical-layer network coding is provided. According to the invention, uncertainty generated by fading channels and noise is described through a basic probability assignment function, then, the uncertainty of received signals is reduced at a receiving end through a Dempster's rule, and finally, reliable transmission signals are obtained through a maximum judgement rule. As compared with the prior sub-optimal algorithm, the method provided by the invention improves bit error rate performance of a relay receiving end well, and simultaneously achieves full diversity gain at the receiving end. Finally, the provided algorithm is subjected to simulation verification, and the result of simulation verification is consistent with theoretical analysis.