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176 results about "Sub populations" patented technology

A subset of a population is called a sub-population. If different sub-populations have different properties, so that the overall population is heterogeneous, the properties and responses of the overall population can often be better understood if the population is first separated into distinct sub-populations.

Aggregating and pooling health related information in a communication system with feedback

The invention provides a method and system for aggregating and pooling information with feedback in a computer communication system. A communication system includes a server device and a set of client devices. Each client device collects information from an associated individual (whether by asking questions of those individuals, or accepting data input from peripheral devices), and transmits that data to a server device. The server device, or some other device at its behest, determines statistical information with regard to that data (such as aggregate, correlation, dispersion, or other measures), and provides that information to a communication channel for distribution to the individuals. The communication channel can include either (1) a broadcast communication channel that members of an affinity group can display, or (2) redistributing the determined statistical measures to associated individuals using the client devices. The statistical measure (such as an aggregate or sum) can be computed and distributed for the entire population, or can be computed and compared for selected sub-populations as a contest.
Owner:HEALTH HERO NETWORK

Methods for identifying multiple epitopes in selected sub-populations of cells

A method for identifying a sub-population within a mixed population of cells is disclosed. The method involves contacting the mixed population of cells with at least one unique binding agent, wherein the at least one unique binding agent is designed to bind to a target molecule present in the sub-population, and wherein the at least one unique binding agent is attached to an epitope specific barcode that represents the identity of the target molecule. The method further involves sequentially attaching two or more assayable polymer subunits to the epitope specific barcode to create unique cell origination barcodes that represent the identities of individual cells to which the at least one unique binding agent has bound; and decoding the epitope specific barcode and cell origination barcodes, thereby identifying the sub-population within the mixed population of cells.
Owner:ROCHE SEQUENCING SOLUTIONS INC

Job-shop scheduling method based on multi-population evolution mechanism

The invention discloses a job-shop scheduling method based on multi-population evolution mechanism, which pertains to the computer field and mainly solves the problem that the present job-shop scheduling method of multi-population genetic algorithm is easy to be trapped into local optimization and poor local search ability. The method comprises the steps of (1) setting parameters and initializing the population; (2) evaluating the chromosomes and the initial memory bank of the population, optimizing the initial memory bank by means of the simulated annealing algorithm; (3) judging whether the termination condition is satisfied, if so, outputting the currently obtained optimal scheduling plan; otherwise, continuing step 4; (4) carrying out the crossover and mutation operation on the chromosomes in each sub-population; (5) communicating the sub-population with the memory bank; and (6) updating the memory bank and optimizing the memory bank by means of the simulated annealing algorithm, and then returning to step (3). The job-shop scheduling method of the invention can obtain the job-shop scheduling plan with high quality, shorten the production time and can be used for selecting the job-shop scheduling plan.
Owner:XIDIAN UNIV

Multi-objective power flow optimization method of VSC-HVDC (voltage source converter-high voltage direct current) containing alternating-current/direct-current system

The invention discloses a multi-objective power flow optimization method of a VSC-HVDC (voltage source converter-high voltage direct current) containing alternating-current/direct-current system, which is characterized by comprising the following steps: establishing a model, selecting to-be-optimized variables and optimization objectives, and determining constraint conditions; setting an initial variable, and giving a to-be-optimized variable range; under the condition of taking the to-be-optimized variables as population individuals in the optimization process, in a hybrid encoding mode, randomly generating an initial population according to the to-be-optimized variable range; calculating the power flow of the alternating-current/direct-current system by using an alternate iterating algorithm; getting the corresponding optimization objective function value of each individual in the population; carrying out rapid non-dominated sorting on the individuals in the population, calculating a virtual fitness, and through selection, crossing and variation processing, generating sub-populations; retaining excellent individuals in parent individuals by using an elitist strategy; judging whether algorithm termination conditions are satisfied, if so, turning to a step 9), and completing optimization; otherwise, turning to the step 4); completing the optimization process, and outputting results. The method has the advantages of scientificity, strong applicability, good effect, and the like.
Owner:NORTHEAST DIANLI UNIVERSITY +1

Method for allocating graticule resource based on paralleling genetic algorithm

The invention relates to a grid resource allocation method based on a parallel genetic algorithm. The method comprises the following steps: firstly, the information is initialized in a main thread, such as task collection, machine collection, an execution time matrix E of the task, and mapping of a sub-task to the machine, etc.; then a plurality of sub threads are generated and mapped to different processors, an initializing sub-population is independently generated by each sub thread, evolutionary computation is performed in parallel, the optimum individual of each generation is transferred to the main thread, the main thread performs comparison, and the optimum individual is retained; when the predetermined generation arrives, the transfer operation between the sub-groups is performed; and the operation of the main thread and all the sub-groups cannot be finished until the termination conditions are met. The genetic algorithm is taken as the most effective heuristic global stochastic searching method, and the solution of the NP problem can be performed. The quality and the speed for the algorithm for solving are improved by the parallel genetic algorithm proposed according to the natural parallelism of the genetic algorithm, and the method is an effective grid energy resource optimization method and favorable for improving the service quality of the grid.
Owner:WUHAN UNIV OF TECH

Computer Network-Interfaced Method for Health Care Provider Active Reach Into Diverse Sub-Population Communities

InactiveUS20140365234A1Improving overall community aspectFacilitates inclusionFinanceTelemedicineSub populationsPublic health
A computer network-interfaced method for public health and health care provider active reach into diverse sub-population communities for the purpose of reducing health care treatment gaps of the population-at-large; comprising a network of computing means for health care provider administrators, a network-interfaced web software registration process requiring member user characteristics and health insurance information to parse members into sub-population communities; provider secure remote access control of network-interfaced computing means of sub-population community members during scheduled consultations, and production, broadcast and storage of protocol-driven life-episodes for actively screening member health care needs and improving social inclusion of sub-population community members.
Owner:COMMUNITY PURSUITS

Distribution network reconstruction method employing parallel genetic algorithm based on undirected spanning tree

The invention relates to a distribution network reconstruction method employing a parallel genetic algorithm based on an undirected spanning tree. The method comprises the following steps: obtaining parameters; performing Monte Carlo simulation sampling; randomly generating an initial population with feasible topology, and setting an initial value of iteration frequency n as 1; performing load flow calculation; calculating a target function value, determining whether constraint conditions are satisfied, if not, returning to the step for re-generating the initial population, and if yes, dividing an existing population into multiple sub populations for performing parallel genetic operation; generating one random permutation P from 1 to Nsub, and establishing a mapping relation between a target sub population i and a source sub population pi, wherein P=[p1, p2,..., pNsub]; replacing the worst individual of each target sub population with an optimal individual of one corresponding source sub population; and determining whether the iteration frequency n reaches requirements, if not, adding one to the iteration frequency and returning to the step of load flow calculation, and if yes, outputting a distribution network reconstruction scheme. Compared to the prior art, the method has the advantages of high calculation efficiency, high integration, close connection with reality and the like.
Owner:SHANGHAI JIAO TONG UNIV +1

Self-adaptive multi-object evolution method adopting constraint cloud workflow scheduling

The invention provides a self-adaptive multi-object evolution method adopting constraint cloud workflow scheduling. The overall detection and local mining capability of the multi-object evolution method can be improved. The multi-object evolution method comprises the steps that S1, the evolution states of populations in the evolution process are detected according to the number of Pareto solutions and Pareto entropies, and corresponding individual evaluation strategy processing constraint conditions are self-adaptively utilized to sort individuals in the populations according to the detected evolution states of the populations in the evolution process, wherein a constraint violation processing method is adopted to process the constraint conditions in individual evaluation strategies; S2, according to individual sorting results, individuals are selected from the populations to perform genetic manipulation, and sub-populations are obtained, wherein genetic manipulation parameters are self-adaptively adjusted according to the evolution states of the populations in the evolution process during genetic manipulation. The self-adaptive multi-object evolution method is suitable for solving the multi-object evolution problem having constraints and can be applied to the technical field of workflow scheduling in a cloud computing environment.
Owner:北京明易达科技股份有限公司

Acquisition and Analysis of Mixed Ion Populations in a Mass Spectrometer

A method of obtaining and analyzing a mass spectrum of a sample comprising components is characterized by: setting values of a first energy level and a second energy level; chromatographically separating the components; ionizing a portion of the separated components to create precursor ions; introducing a first portion of the precursor ions into a collision or reaction cell and generating a first sub-population of ions corresponding to the first energy level; introducing a second portion of the precursor ions into the cell and generating a second sub-population of ions corresponding to the second energy level; transferring a mixture of the first and second sub-populations of ions into a mass analyzer; producing an analysis of the ions of the mixture; varying the value of at least one of the first and the second energy levels according to a pre-determined cyclical variation; repeating various above steps; and analyzing the time-variation of the analyses.
Owner:THERMO FINNIGAN

Method for improving standard shuffled frog leaping algorithm

The invention discloses a method for improving a standard shuffled frog leaping algorithm.The method comprises the steps of initializing parameters; calculating the adaptive value of each frog individual, and finding the adaptive value and position of the global optimum frog individual of a frog population; conducting optimum drawdown ranking on the frog population; conducting dividing for obtaining frog sub-populations; finding the positions of the optimum and the worst frog individual of each frog sub-population; conducting updating operation on the position of the worst frog individual of each frog sub-population; calculating the adaptive value of the frog individual with the position updated in each frog sub-population, and finding the global optimum adaptive value and the position of the frog population at this moment; implementing prediction of the global optimum adaptive value of the frog population obtained after iteration is completed next time, and furthermore adjusting the movement step-length variable coefficient dj and skip among steps; judging whether the ending conditions are met or not.By means of the method, the defects that at the later stage, the convergence rate of the standard shuffled frog leaping algorithm is severely lowered, convergence precision is insufficient, and the algorithm is prone to getting into local optimum are overcome.
Owner:HEBEI UNIV OF TECH

Resource scheduling method and system in cloud computing system

The invention discloses a resource scheduling method in a cloud computing system. According to the method, the position of an updating frog is computed by the aid of a leapfrog updating formula when each sub-population is locally searched, the fitness of the updating frog is computed to judge whether the fitness of the updating frog is superior to that of the worst frog or not, the position of the updating frog replaces that of the worst frog if the fitness of the updating frog is superior to that of the worst frog, the position of the optimal frog in the whole population replaces that of the worst frog if not, whether the fitness of the updated frog is superior to that of the worst frog or not is judged, the position of the updated frog replaces that of the worst frog if the fitness of the updated frog is superior to that of the worst frog, a new step length is generated by a double learning factor formula if not, the new step length is mutated according to mutation probability to obtain the position of the updated frog and replace the position of the worst frog, and the fitness of the updated frog is computed. The method can achieve good performances in optimal time span and load balance for task scheduling. The invention further discloses a resource scheduling system in the cloud computing system.
Owner:GUANGDONG UNIV OF TECH
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