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36 results about "Local adaptation" patented technology

Local adaptation is when a population of organisms has evolved to be more well-suited to its environment than other members of the same species. This occurs due to differential pressures of natural selection on populations from different environments. For example, populations of a species that lives within a wide range of temperatures may be locally adapted to the warmer or cooler climate where they live. More formally, a population is said to be locally adapted if organisms in that population have differentially evolved as compared to other populations within their species in response to selective pressures imposed by some aspect of their local environment. Local adaptation is often determined via reciprocal transplant experiments, where organisms from one population are transplanted into another population, and vice versa, and their fitnesses measured. If the foreign (transplanted) organisms have lower fitness than the native organisms in an environment, then the native population can be said to be locally adapted.

Global Classifier with Local Adaption for Objection Detection

Aspects of the present invention include object detection training systems and methods and using object detection systems and methods that have been trained. Embodiments presented herein include hybrid learning approaches that combine global classification and local adaptations, which automatically adjust model complexity according to data distribution. Embodiments of the present invention automatically determine model complexity of the local learning algorithm according to the distribution of ambiguous samples. And, embodiments of the local adaptation from global classifier avoid the common under-training problem for local classifier.
Owner:SEIKO EPSON CORP

Device and method of automated construction of emergency flight path for aircraft

The invention relates to a flight management system for manned or unmanned aircraft having to face an emergency situation such as hijacking of the aircraft, medical emergencies, situations of failures affecting the propulsion, pressurization or communication functions for example. It provides for a device and process for automatically or semi-automatically generating a flight plan compatible with international regulations and their national or local adaptations with possibilities of optimization according to navigation parameters.
Owner:THALES SA

Regional progressive meshes

A regional progressive mesh provides support for real-time rendering of large-scale surfaces with locally adapting surface geometric complexity according to changing view parameters. The regional progressive mesh is constructed by subdividing an initial detailed mesh one or more times into multiple sub-regions as an iterative or recursive process. Each sub-region is separately simplified, and the localized transformations recorded in separate segments in a sequence of mesh refinement transformations that form the progressive mesh representation. The resulting regionalized organization of mesh refinement transformations reduces the working set of memory pages containing progressive mesh data needed for real-time view-dependent adaptation and rendering of the mesh surface. An exact approximate error measurement of a vertex split transformation also is defined as the maximum height deviation at enumerated vertices in the open neighborhood of the transformation relative to a regular triangulation of grid points, where the enumerated vertices include the grid points internal to the faces adjacent the split vertex and the grid line crossings internal to edges adjacent the split vertex.
Owner:MICROSOFT TECH LICENSING LLC

Self-adapting regular super resolution image reconstruction method for maintaining edge clear

The invention discloses a self-adaptive regularized super-resolution image reconstruction method which can keep marginal definition, which mainly solves the problem that the prior method has edge fog in reconstruction of a degraded image. The method comprises the following steps: an imaging model is constructed; on the basis of an unconstrained objective function constructed by a Lagrangian multiplier method, gradient is increased to approach a bound term; the objective function is expanded; L1 norm is adopted to measure a data approximation term; a self-adaptive bilateral total variation model which can carry out local adaptive control on the smoothing effect is utilized to construct a self-adaptive regular term; a gradient approximation term is added to be as constraint of gradient consistency; edge information is kept; the self-adaptive regular term and a gradient consistency bound term are introduced as constraint conditions; an expanded Lagrangian objective function is constructed and optimized; and an optimized unconstrained objective function is utilized to reconstruct an image, thereby obtaining a high-resolution image of which the edge is kept. The method can keep image edge clear, can inhibit noise and is suitable for restoration treatment on the degraded image.
Owner:XIDIAN UNIV

Dictionary database-based adaptive image super-resolution reconstruction method

The invention discloses a dictionary database-based adaptive image super-resolution reconstruction method in the field of image processing. The dictionary database-based adaptive image super-resolution reconstruction method comprises the steps of: adaptively selecting a matched dictionary from a dictionary database according to a characteristic vector of each low-resolution image block, if the matching fails, re-training to obtain a proper dictionary, updating the dictionary into the dictionary database, then carrying out super-resolution reconstruction on the blocks by using the dictionary to obtain image blocks with high resolution, and finally, recombining all blocks to obtain a high-resolution image. The dictionary database-based adaptive image super-resolution reconstruction method is test in a face image, results prove that the method is superior to a method using a single dictionary in term of the image reconstructing effect, training image blocks with higher matching degree can be screened out in a process of training a local adaptive dictionary; and since many matched image blocks exist, prior information of a training set is sufficient amd a reconstructing effect is greatly improved compared with that of the method using the single dictionary.
Owner:SHANGHAI JIAO TONG UNIV

Protein complex identification method based on key protein and local adaptation

The invention discloses a protein complex identification method based on key protein and local adaptation. Based on the importance of the key protein to life activities of organisms and the topological property of a protein interaction network, the invention discloses the protein complex identification method (EPOF) based on key protein and locally adapted protein by using the key protein as a seed. The protein complex identification method not only can be applied to a non-weighted protein interaction network, but also can be applied to a weighted protein interaction network. The protein complex identification method can be used for recognizing the protein complex more accurately only according to the protein interaction information and the key protein information, and predicting a large quantity of protein complexes in one step, and solves the problems of high cost, high time consumption and the like of the chemical experiment method.
Owner:CENT SOUTH UNIV

Multiple-wind-power-plant correlation modeling method based on adaptive multi-variable nonparametric kernel density estimation

The invention discloses a multiple-wind-power-plant correlation modeling method based on adaptive multi-variable nonparametric kernel density estimation, and belongs to the technical field of multidimensional variable correlation research. The method comprises the following steps that: S1: establishing a multi-variable nonparametric kernel density estimation model of a wind power plant; S2: constructing a bandwidth optimization model; and S3: constructing a bandwidth solving method of the multi-variable nonparametric kernel density estimation model of the wind power plant on the basis of ordinal optimization. By use of a method, a modeling process is practical and simple, correlation among a plurality of random variables can be quickly and efficiently modelled. Compared with a traditional parametric estimation method based on a copula function, the method is higher in accuracy and applicability, and a local adaptation problem of a traditional multi-variable nonparametric kernel density estimation method is favorably solved.
Owner:CHINA THREE GORGES UNIV

Method of producing a heterostructure with local adaptation of the thermal expansion coefficient

A method of producing a heterostructure by bonding at least one first substrate having a first thermal expansion coefficient onto a second substrate having a second thermal expansion coefficient, with the first thermal expansion coefficient being different from the second thermal expansion coefficient. Prior to bonding, trenches are formed in one of the two substrates from the bonding surface of the substrate. The trenches are filled with a material having a third thermal expansion coefficient lying between the first and second thermal expansion coefficients.
Owner:SOITEC SA

Synergic variation differential evolutionary algorithm for high-dimensional parameter space wave form inversion

The invention discloses a synergic variation differential evolutionary algorithm for high-dimensional parameter space wave form inversion. According to the algorithm, a thought of resolving-coordination is introduced to the differential evolutionary algorithm, a high-dimensional unit is resolved to a series of sub components and a partial fitness function is introduced for evaluating each sub component. A variation direction of each sub component is guided through partial fitness in vibration operation and each sub component is adjusted through overall situation in a selection operation so that co-evolution is achieved. Compared with a common simulated annealing method and a genetic algorithm, the synergic variation differential evolutionary algorithm is more suitable for the high-dimensional parameter space wave form inversion. Under the conditions that a layer is thin and the number of to-be-inversed parameters is large, a solution close to a true value can be researched through the synergic variation differential evolutionary algorithm. In addition, the rate of convergence of the synergic variation differential evolutionary algorithm is not sensitive to increase of a dimensionality so that the rate of the convergence is fast when the dimensionality is high.
Owner:XI AN JIAOTONG UNIV

Multi-constraint service selection method and device based on global QoS decomposition

The invention relates to a multi-constraint service selection method and device based on global QoS decomposition, which is realized by establishing a single object optimization model with a number of constraints. The method comprises the steps that a corresponding dependency set and collision set are established for each candidate service according to the service dependency transmission characteristic; the global QoS constraint is decomposed into local QoS constraints corresponding to each service class; candidate services which do not satisfy the local QoS constraints under the service class are filtered; all filtered candidate services are checked, and the dependency set and collision set of the remaining candidate services are updated; an adaptive replacement method is used to carry out quality scale combination replacement in an unresolved state; the local fitness of each candidate service is calculated; and the candidate service with the greatest local adaptability in each service class is selected to form the final combination service. According to the invention, the complexity and running time are greatly optimized; the real-time demand of a user is satisfied; the scale of a candidate service space is narrowed; and the quality and performance of the network combination service are effectively ensured.
Owner:THE PLA INFORMATION ENG UNIV

Silicon wafer surface topography reconstruction method based on B-spline

InactiveCN103295203AMinimize the number of sampling pointsSolve redundancyImage enhancementReconstruction methodAdaptive refinement
The invention provides a silicon wafer surface topography reconstruction method based on B-spline. The silicon wafer surface topography reconstruction method based on the B-spline comprises firstly fitting an input triangular mesh boundary, and then giving a boundary curve to perform surface fitting of an interpolation, and generating a first level B-spline surface; secondly, performing local adaptive refinement fitting on an error transfinite portion in an upper level B-spline surface and repeatedly performing local refinement fitting in this way until a given error is met; and finally, adding the multilevel B-spline surface with the offset to a base plane to obtain a fitting result. The silicon wafer surface topography reconstruction method based on the B-spline can simultaneously meet overall fitting and local adaptation of surface reconstruction, and effectively avoids data redundancy; and is strong in robustness and has significant effects for solving non-linear problems and restraining fuzzy noises; and the reconstructed surface is smooth and burr-free, so that the method can better meet response frequency requirements of actual motion of a motor.
Owner:INST OF OPTICS & ELECTRONICS - CHINESE ACAD OF SCI

Community self-organizing detection method for power network fault diagnosis

The invention discloses a community self-organizing detection method for power network fault diagnosis. The method comprises the steps of firstly, collecting network characteristic parameters of power networks, then describing the power networks as weighted network models, constructing local fitness and global fitness functions, starting from grouped solutions of the power networks, which are generated randomly, calculating local fitness of each power node, sequencing the local fitness, selecting the nodes with the poor local fitness according to an expansion evolution probability distribution function, transferring the nodes with the poor local fitness to another group of networks to generate new solutions, comparing global fitness values of the new solutions and the current solutions, reserving the best solutions in the new solutions and the current solutions, enabling the new solutions to serve as initial solutions for the next iteration to repeat above optimization processes until preset end conditions are met, and finally, analyzing and outputting community self-organizing detection results which are used for power network fault diagnosis. Compared with conventional methods, the method has the advantages of being a few in adjusting parameter, simple in detection process, easy to implement and high in detection efficiency and detection precision.
Owner:GUANGDONG ZHICHENG CHAMPION GROUP

System and method for automated hairstyle processing and hair cutting device

The present disclosure relates to an automated hairstyle processing method, an an automated hairstyle processing system, and an automated hair cutting device, the system (10) comprising a memory unit (48) arranged to store a predefined hairstyle model (90) including hair property representing values and body shape representing values, particularly head shape representing values, a sampling unit (76) arranged to sample an actual body shape portion, particularly an actual head shape, of a to be treated subject (12), involving detecting deviations from a model body shape portion of the predefined hairstyle model, a processing unit (42) arranged to adapt a hair property model (94) of the predefined hairstyle model, in case deviations between the actual body shape and the model body shape portion are detected, so as to compensate the actual body shape deviations, the adaptions to the hair property model (94) being local adaptations.
Owner:KONINKLJIJKE PHILIPS NV

Method and device for single sample face identification based on local convolution feature combination representation

The present invention is suitable for the computer vision and mode identification technology field, and provides a method and device for single sample face identification based on local convolution feature combination representation. The method comprises: extracting corresponding image blocks to be identified at feature points with preset quantity of a face image to be identified in a feature point division mode; putting each identification image to be identified into a local adaptation convolution network corresponding to each feature point to extract the features of each feature point; calculating combination representation of the features of all the feature points on the face image to be identified according to a changing dictionary and a query dictionary in a category, and calculating the representation coefficient of the features of all the feature points in the combination representation according to a projection matrix and a temporary matrix; and according to the representation coefficient, the changing dictionary in the category and the features of each feature point on the face image to be identified, determining the identity of the face image to be identified so as to effectively improve the face identification robustness, reduce the face identification time consumption and effectively improve the face identification efficiency and identification accuracy.
Owner:SHENZHEN UNIV

Forest tree microscopic carbon sink metering assimilation box parameter measuring instrument

The invention discloses a forest tree microscopic carbon sink metering assimilation box parameter measuring instrument. The measuring instrument is divided into two parts, namely, a host part and a slave part; the host part mainly comprises a power supply module, a single-chip microcomputer processing module, a TFT touch screen display module, a communication interface module and so on; the slave part includes a power supply module, a single-chip microcomputer processing module, a communication interface module, a tree diameter growth measurement module, a temperature and humidity measurement interface module, an illumination intensity measurement module, a CO2 concentration measurement interface module, a data storage module and so on. With the forest tree microscopic carbon sink metering assimilation box parameter measuring instrument of the invention adopted, multi-parameter measurement can be realized. The forest tree microscopic carbon sink metering assimilation box parameter measuring instrument has the advantages of high automation degree, high local adaptation, convenience in measuring place replacement and the like.
Owner:CHINA JILIANG UNIV

Information acquisition system and method enabling field detection equipment to be flexibly connected

The embodiment of the invention provides an information acquisition system and method enabling field detection equipment to be flexibly connected. When the detection equipment is connected to data acquisition management equipment, self-described data packets are sent, automatic adaptation is carried out after the detection equipment is connected to the data acquisition management equipment, and itis achieved that the detection equipment with different varieties is dynamically connected to the same data acquisition management equipment. Secret data transmission is carried out without the Internet processing technology, the functions such as local registration, local adaptation and local analysis under the local area data transmission network condition are achieved, secret data informationleakage caused by universal means such as network side adaptation and network data processing is avoided, the actual problems such as corresponding equipment adaptation and data access can be solved in field detection of the portable heavy metal detection equipment, and a series of operations such as local registration, adaptation and data frame analysis of the detection equipment are completed under the condition that the Internet is not available.
Owner:BEIJING RES CENT FOR INFORMATION TECH & AGRI

Method for controlling optimization through self-organized extremum optimization process

InactiveCN104361204ASolve the problem that the entire solution space cannot be searchedSpecial data processing applicationsControl objectiveExtremal optimization
A method for controlling optimization through self-organized extremum optimization process is used for solving continuous function optimization through the self-organized extremum optimization process, and the solved optimum solution is used as control parameters. The self-organized extremum optimization process comprises the following steps: step 1, determining the local fitness function of a continuous function f(x) according to a control objective; step 2, generating the initial solution s of the continuous function f(x) at random and setting the current optimum solution sbest; step 3, working out the local fitness of each individual si (i equals to 1, ..., m) aiming at the current initial solution; step 4, finding out the local fitness with the maximum fitness value; step 5, structurally changing the neighbourhood space N(s) of the individual sj corresponding to the local fitness with the maximum fitness value, selecting a neighbourhood solution s' belonging to N(s), and taking the selected neighbourhood solution as a new solution unconditionally; step 6, substituting the new solution and the current optimum solution sbest into the continuous function respectively so as to judge that whether the formula that f(s') is less than or equal to f(sbest) is workable or not, if the formula that f(s') is less than or equal to f(sbest) is workable, setting the new solution to be the final optimum solution, and if the formula that f(s') is less than or equal to f(sbest) is not workable, returning to step 2.
Owner:SHANGHAI DIANJI UNIV

An Extremum Optimization Method for Solving the Maximum Satisfaction Problem

InactiveCN102289580AGuidingEasy to obtain near optimal solution or even global optimal solutionSpecial data processing applicationsLocal variableExtremal optimization
The invention discloses an extremum optimization method for solving the maximum satisfiability problem. The method defines local fitness and global fitness functions that meet the requirements of the extremum optimization method according to the principle of decomposability and linearity; uses Bose-Einstein probability distribution to construct optimization The initial solution; when selecting poor local variables for mutation, multiple probability distributions such as exponential distribution or mixed distribution are used as the extended evolution probability distribution. Compared with the traditional optimization method, the optimization process of this method is more instructive, and it is easier to obtain a near-optimal solution or even a global optimal solution. Its principle is simple and clear, with fewer adjustment parameters, simple design, and easy implementation.
Owner:WENZHOU UNIVERSITY

A community self-organization detection method for power network fault diagnosis

The invention discloses a community self-organizing detection method for power network fault diagnosis. The method comprises the steps of firstly, collecting network characteristic parameters of power networks, then describing the power networks as weighted network models, constructing local fitness and global fitness functions, starting from grouped solutions of the power networks, which are generated randomly, calculating local fitness of each power node, sequencing the local fitness, selecting the nodes with the poor local fitness according to an expansion evolution probability distribution function, transferring the nodes with the poor local fitness to another group of networks to generate new solutions, comparing global fitness values of the new solutions and the current solutions, reserving the best solutions in the new solutions and the current solutions, enabling the new solutions to serve as initial solutions for the next iteration to repeat above optimization processes until preset end conditions are met, and finally, analyzing and outputting community self-organizing detection results which are used for power network fault diagnosis. Compared with conventional methods, the method has the advantages of being a few in adjusting parameter, simple in detection process, easy to implement and high in detection efficiency and detection precision.
Owner:GUANGDONG ZHICHENG CHAMPION GROUP
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