2001results about "Genetic models" patented technology

Dynamically filtering and classifying messages, as good messages, bulk periodicals, or spam. A regular expression recognizer, and pre-trained neural networks. The neural networks distinguish “likely good” from “likely spam,” and also operate at a more discriminating level to distinguish among the three categories above. A dynamic whitelist and blacklist; sending addresses are collected when the number of their messages indicates the sender is good or a spammer. A dynamically selected set of regular expressions input to the neural networks.

A system and method for automatic creation of digital image albums. A Page Creator Module utilizes a genetic engine and a layout evaluation module. The genetic engine evolves a group of images to a plurality of album pages, based on certain layout criteria. The evaluation module calculates layout criteria and compares them with user preferences. When an acceptable image / page layout has been generated, the image / page assignments are transferred to an Image Placement Module. The Image Placement Module utilizes a second genetic engine, which evolves various criteria to generate page layouts genetic structures. These structures define the location, scale, and rotation of images placed on a given page. A layout evaluation module calculates and compares these layouts with certain other preferences and page requirements. When a suitable layout has been generated, a final album output is generated, which may be displayed, printed, or otherwise transferred for subsequent utilization.

A system for generating a schedule by generating assignments for the tasks of a project and sequentially scheduling the individual assignments to available resources. First, input information is received which includes a resource calendar and a task list. A resource calendar identifies the resources available to work on a project and any constraints that are associated with the resources. A task list identifies the tasks that must be performed and any constraints that are associated with the tasks. At a minimum, the constraints associated with the tasks must identify each of the resources assigned to the task, and the work-amount that each resource must perform. Next, assignments are generated for each of the tasks. Each of the assignments identifies a specific resource and the work-amount required by the specific resource. Finally, each of the assignments are scheduled in accordance with the provided resource constraints identified in the resource calendar. The resulting schedule maximizes the utilization of the resources by scheduling on an assignment basis. The assignments are individually scheduled into the next available time-slot of the resources, thus, eliminating idle time where a resource is under-utilized.

The present invention is a biometric security system and method operable to authenticate one or more individuals using physiological signals. The method and system may comprise one of the following modes: instantaneous identity recognition (MR); or continuous identity recognition (CIR). The present invention may include a methodology and framework for biometric recognition using physiological signals and may utilize a machine learning utility. The machine learning utility may be presented and adapted to the needs of different application environments which constitute different application frameworks. The present invention may further incorporate a method and system for continuous authentication using physiological signals and a means of estimating relevant parameters.

A system and method for tracking a user history, for presentation thereof within a browser display. An executable software construct operates at a client machine to trap object references, which are then transmitted to a server. The server analyzes the object references and organizes them into a display structure. The display structure is then displayed within the browser, including hyperlinks to allow the user to select a prior system state to which he seeks to return. Preferably, the software construct also manages objects associated with the object reference, for example cookies associated with URLs, in order to assure full definition of the desired state. The display structure may also be provided to browsers distinct from the originating browser.

Solutions for solving a problem experienced by a user are retrieved. In response to receiving a query from the user describing the problem, relevant candidate solutions to the problem are sent to the user. In response to receiving a selection of one relevant candidate solution from the relevant candidate solutions, instructions steps within the one relevant candidate solution selected by the user are analyzed. An instruction step similarity is calculated between the instruction steps within the one relevant candidate solution selected and other instructions steps within other solutions stored in a storage device. Then, similar solutions are sent to the user containing similar instruction steps to the instruction steps contained within the one relevant candidate solution selected based on the calculated instruction step similarity.

The present invention relates to methods of assessing disease susceptibility associated with dietary and lifestyle risk factors. The invention provides for analysis of alleles at loci of genes associated with lifestyle risk factors, and the disease susceptibility profile of an individual is determined by reference to datasets which further match the risk factor with lifestyle recommendations in order to produce a personalized lifestyle advice plan.

A genetic algorithm (GA) approach is used to adapt a wireless radio to a changing environment. A cognitive radio engine implements three algorithms; a wireless channel genetic algorithm (WCGA), a cognitive system monitor (CSM) and a wireless system genetic algorithm (WSGA). A chaotic search with controllable boundaries allows the cognitive radio engine to seek out and discover unique solutions efficiently. By being able to control the search space by limiting the number of generations, crossover rates, mutation rates, fitness evaluations, etc., the cognitive system can ensure legal and regulatory compliance as well as efficient searches. The versatility of the cognitive process can be applied to any adaptive radio. The cognitive system defines the radio chromosome, where each gene represents a radio parameter such as transmit power, frequency, modulation, etc. The adaptation process of the WSGA is performed on the chromosomes to develop new values for each gene, which is then used to adapt the radio settings.

A new method, system and apparatus is provided that enables muscle signals that correspond to muscle contractions to be mapped to one or more functions of an electronic device such as a prosthetic device or gaming apparatus. Muscle signals are classified in real-time from self-selected intentional movements. A self-training protocol allows users to select and label their own muscle contractions, and is operable to automatically determine the discernible and repeatable muscle signals generated by the user. A visual display means is used to provide visual feedback to users illustrating the responsiveness of the system to muscle signals generated by the user.

A Virtual Design Module (VDM) used in a networked design environment generates manufactured product designs that are near optimal in terms of cost and production cycle time by using design data files containing alternative parts and manufacturers information. Numerous product design alternatives are considered and evaluated in terms of design-manufacturing-parts-supplier feasibility and real-time information on cost and production cycle time for realization. The VDM generates a population of new designs with appropriate board design information to allow for design-manufacturer-supplier decision making and determines the feasibility of each member of the current generation of designs and rejects designs that are not feasible. The VDM triggers Mobile Software Agents (MSA) that obtain data for parts availability, cost, lead time and manufacturer data for manufacturing availability, cost and lead time for each feasible member of the current generation of designs and return the data. In one application for printed circuit board design, the VDM evaluates each member of the current generation of designs by calculating cost, lead-time and value using a J function. The VDM then improves board designs through selection and use of board design modifiers. The process continues until optimized designs are obtained. Optimized board designs are output as results to an operator.

A computer implemented method, system and / or program product determine capacity planning of resources allocation for an application scheduled to execute on a virtual machine from a set of multiple applications by computing a mean associated with a pool of pre-defined resources utilization over a time interval; computing a variance associated with the pool of pre-defined resources utilization over the same time interval; identifying a set of resource to execute the scheduled application from the pool of pre-defined resources, wherein the pool of pre-defined resources is created from a pre-defined Service Level Agreement (SLA); and allocating a set of fixed resources from the pool of pre-defined resources to execute the application based on the mean resource utilization.

A genetic algorithm (GA) approach is used to adapt a wireless radio to a changing environment. A cognitive radio engine implements three algorithms; a wireless channel genetic algorithm (WCGA), a cognitive system monitor (CSM) and a wireless system genetic algorithm (WSGA). A chaotic search with controllable boundaries allows the cognitive radio engine to seek out and discover unique solutions efficiently. By being able to control the search space by limiting the number of generations, crossover rates, mutation rates, fitness evaluations, etc., the cognitive system can ensure legal and regulatory compliance as well as efficient searches. The versatility of the cognitive process can be applied to any adaptive radio. The cognitive system defines the radio chromosome, where each gene represents a radio parameter such as transmit power, frequency, modulation, etc. The adaptation process of the WSGA is performed on the chromosomes to develop new values for each gene, which is then used to adapt the radio settings.

The invention discloses a three-dimensional formation reconfiguration method for multiple unmanned aerial vehicles based on particle swarm optimization and genetic algorithm. The method considers the position of the unmanned aerial vehicle in the ground coordinates and the speed, track angle and course angle of the unmanned aerial vehicle when establishing a formation model, carries out subsection linear disposal of the control input of each flying unit in the unmanned aerial vehicle, replaces the approximate subsection linear control input with the continuous control input, then carries out global search by the genetic algorithm, subsequently carries out partial searching by the particle swarm optimization algorithm, on the base thereof, the particle swarm optimization is used to guide the genetic algorithm to search a global optimum solution so as to figure out the subsection linear control input. Compared with the traditional method, the method provided by the invention has good real-time performance and rapidity and can be used for solving the formation reconfiguration problem of multiple space robots under complex and dynamic environment.

Quantum processor based techniques minimize an objective function for example by operating the quantum processor as a sample generator providing low-energy samples from a probability distribution with high probability. The probability distribution is shaped to assign relative probabilities to samples based on their corresponding objective function values until the samples converge on a minimum for the objective function. Problems having a number of variables and / or a connectivity between variables that does not match that of the quantum processor may be solved. Interaction with the quantum processor may be via a digital computer. The digital computer stores a hierarchical stack of software modules to facilitate interacting with the quantum processor via various levels of programming environment, from a machine language level up to an end-use applications level.

Described herein are systems and methods for normalizing data without the use of external controls. Also described herein are systems and methods for analyzing cluster data, such as genotyping data, using an artificial neural network.

Dynamically filtering and classifying messages, as good messages, bulk periodicals, or spam. A regular expression recognizer, and pre-trained neural networks. The neural networks distinguish “likely good” from “likely spam,” and also operate at a more discriminating level to distinguish among the three categories above. A dynamic whitelist and blacklist; sending addresses are collected when the number of their messages indicates the sender is good or a spammer. A dynamically selected set of regular expressions input to the neural networks.

The present invention provides an electronic nose device based on chemically sensitive field effect transistors. In particular, the sensors of the electronic nose device are composed of non-oxidized, functionalized silicon nanowires which can detect volatile organic compounds with very high sensitivity. Methods of use in diagnosing diseases including various types of cancer are disclosed.

The invention discloses a wind power forecasting method based on a genetic algorithm optimization BP neural network, comprising the steps: acquiring forecasting reference data from a data processing module of a wind power forecasting system; establishing a forecasting model of the BP neural network to the reference data, adopting a plurality of population codes corresponding to different structures of the BP neural network, encoding the weight number and threshold of the neural network by every population to generate individuals with different lengths, evolving and optimizing every population by using selection, intersection and variation operations of the genetic algorithm, and finally judging convergence conditions and selecting optimal individual; then initiating the neural network, further training the network by using momentum BP algorithm with variable learning rate till up to convergence, forecasting wind power by using the network; and finally, repeatedly using a forecasted valve to carry out a plurality of times of forecasting in a circle of forecast for realizing multi-step forecasting with spacing time interval. In the invention, the forecasting precision is improved, the calculation time is decreased, and the stability is enhanced.

A method and apparatus for data analysis according to various aspects of the present invention is configured to automatically identify a characteristic of a component fabrication process guided by characteristics of the test data for the components.

Methods for modeling the secondary path of an ANC system to improve convergence and tracking during noise control operation, and their associated uses are provided. In one aspect, for example, a method for modeling a secondary path for an active noise control system is provided. Such a method may include receiving a reference signal, filtering the reference signal with an initial secondary path model to obtain a filtered reference signal, calculating an autocorrelation matrix from the filtered reference signal, and calculating a plurality of eigenvalues from the autocorrelation matrix. The method may further include calculating a maximum difference between the plurality of eigenvalues and iterating a test model to determine an optimized secondary path model having a plurality of optimized eigenvalues that have a minimized difference that is less than the maximum difference of the plurality of eigenvalues, such that the optimized secondary path model may be utilized in the active noise control system.

A method or apparatus for changing a performance level of a disk drive from an initial performance level to a target performance level, wherein the disk drive includes a profile table. The method including determining an initial performance level, determining a target performance level, determining constant offset values that cause the performance level of the disk drive to match the target performance level, and programming a constant offset table of the profile table with the constant offset values.

The invention provides an optimization device for a unitary apparatus that can obtain optimum characteristics as a combined apparatus, without losing user's selectivity and unitary apparatus's versatility. The optimization device includes an optimization process section that optimizes dynamic characteristics of the unitary apparatus using genetic algorithms and fuzzy inference, with functional characteristics of a combined apparatus as evaluation reference.

Mechanisms and techniques provide a system for tracking and reporting on the resolution of problems across multiple product areas. The system can receive a first problem definition and can define a first work item identifying a respective first resolution associated with the first problem definition. The system can further define a second work item identifying a respective second resolution associated with the first problem definition. Work items can be automatically generated by the system or users may manually create the work items. The system can also receive at least one work item update for at least one of the first and second work item. The work item update alters a resolution state associated with either the first and second work items for which the work item update is received. The system can also provide a problem resolution report for the first problem definition based upon a correlation of resolution states associated with at least the first and second work items.

A method for comparing data sequences includes accepting first and second data sequences of data elements. A distance matrix is computed. The matrix includes rows and columns of matrix elements, describing distances between the data elements of the first sequence and the data elements of the second data sequence. The distance matrix is reshaped by applying successive, incremental shifts to the rows or columns so as to produce a reshaped matrix. A best-score path through the reshaped matrix is calculated using vector operations, so as to quantify a similarity between the first and second data sequences. Due to vectorization, a significant increase in computation speed is achieved in both software and hardware implementations.

Systems and methods of obtaining a set of better converged and diversified Pareto optimal solutions in an engineering design optimization of a product (e.g., automobile, cellular phone, etc.) are disclosed. According to one aspect, a plurality of MOEA based engineering optimizations of a product is conducted independently. Each of the independently conducted optimizations differs from others with parameters such as initial generation and / or evolutionary algorithm. For example, populations (design alternatives) of initial generation can be created randomly from different seed of a random or pseudo-random number generator. In another, each optimization employs a particular revolutionary algorithm including, but not limited to, Nondominated Sorting Genetic Algorithm (NSGA-II), strength Pareto evolutionary algorithm (SPEA), etc. Furthermore, each independently conducted optimization's Pareto optimal solutions are combined to create a set of better converged and diversified solutions. Combinations can be performed at one or more predefined checkpoints during evolution process of the optimization.

A computer implemented method of constructing a computer implemented knowledge base, of evaluating a plurality of invoices, of knowledge refinement and generation, as well as a computer implemented knowledge base for analyzing a plurality of invoices. The methods comprise receiving the invoices, semantic and logically analyzing them to identify the invoice items (parameters and algorithms of service providers, billing plans, user profile, consumption pattern and debits) and relations connecting them and construct the knowledge base. The knowledge base comprises a hierarchic taxonomy of billing plans related to services of any domain (telecommunications services, banking, insurance, utilities etc.) and a computer implemented generic invoice constructed in reverse engineering logic for simulating debits. Debit simulations are done in order to achieve: 1. recommendations for optimal billing plans. 2. Recommendations for possible detected billing errors. 3. recommendations concerning new plans and / or services, and their financial implications Improving the knowledge base may use genetic algorithms based on an analogous hierarchic structure of the taxonomy to a genetic hierarchy, and may proceed by refining billing plans and comparing the resulting debits. Novel Semantic-web and Artificial Intelligence (AI) methods are used.

The invention discloses a MC / DC (Modified Condition Decision Coverage) test data automatic generation method based on a genetic algorithm, comprising the following steps of: statically analyzing a tested program to generate a control flow graph, a data flow graph, an abstract syntax tree and an abstract analysis tree; generating a MC / DC test case expected result set; executing code instrumentation on the tested program; constructing a fitness function; randomly generating the test data, and checking whether the test data satisfies an expected execution path; and obtaining proper test data through genetic operations, such as selection, crossing, mutation and the like of the genetic algorithm. In the method, for construction of the fitness function, optimization of approximate-level fitness evaluation by a method of obtaining a control node directly or indirectly influencing defective node traversing through data dependency is proposed according to the thought of a chaining method and based on the conventional fitness function. The method has greater practical value for testing a system with complex logical relations.