Abstract: A clock-less asynchronous processing circuit or system utilizes a self-clocked generator to adjust the processing delay (latency) needed/allowed to the processing cycle in the circuit/system. The timing of the self-clocked generator is dynamically adjustable depending on various parameters. These parameters may include processing instruction, opcode information, type of processing to be performed by the circuit/system, or overall desired processing performance. The latency may also be adjusted to change processing performance, including power consumption, speed etc.

Abstract: Artificial Immune Systems (AIS) including the Dendritic Cell Algorithm (DCA) are an emerging method to detect malware in computer systems. A DCA module may receive an output or signal from multiple indicators concerning the state of at least a portion of the system. The DCA module is configured to combine the plurality of signals into a single signal vector. The DCA module may be configured to sort the received signals based on signal type and magnitude of each signal. The DCA module may then use a decay factor to weight the received signals so that a large number of “nominal” signals do not drown out a small number of “strong” signals indicating a malware attack. The decay factor may be exponentially increased each time it is applied so that all received signals are considered by the DCA module, but so that the “nominal” signals may have a minimal effect.

Abstract: A method of providing reservation status relating to a group of objects includes providing a database for containing (i) availability data describing availability of at least one of the group of objects, and (ii) reservation data describing allocation of at least one of the group of objects. The availability data and the reservation data are stored in sparse form. The method further includes extracting, from the database, availability data and reservation data corresponding to a predetermined period of time, and combining the extracted availability data and reservation data to form windowed data in a dense format. The method also includes receiving the windowed data and providing the windowed data in a bit-vector view, and sampling the windowed data in the bit-vector view to produce sampled data. The sampled data provides the reservation status as a static view of the windowed data in the bit-vector view.

Abstract: Disclosed are methods and systems for significantly compressing sparse multidimensional ordered series data comprised of indexed data sets, wherein each data set comprises an index, a first variable and a second variable. The methods and systems are particularly suited for compression of data recorded in double precision floating point format.

Abstract: Spatial pyramid pooling (SPP) layers are combined with convolutional layers and partition an input image into divisions from finer to coarser levels, and aggregate local features in the divisions. A fixed-length output may be generated by the SPP layer(s) regardless of the input size. The multi-level spatial bins used by the SPP layer(s) may provide robustness to object deformations. An SPP layer based system may pool features extracted at variable scales due to the flexibility of input scales making it possible to generate a full-image representation for testing. Moreover, SPP networks may enable feeding of images with varying sizes or scales during training, which may increase scale-invariance and reduce the risk of over-fitting.

Abstract: A clock-less asynchronous processing circuit or system having a plurality of pipelined processing stages utilizes self-clocked generators to tune the delay needed in each of the processing stages to complete the processing cycle. Because different processing stages may require different amounts of time to complete processing or may require different delays depending on the processing required in a particular stage, the self-clocked generators may be tuned to each stage's necessary delay(s) or may be programmably configured.

Abstract: Computerized contextual analysis systems and methods suitable for monitoring situations, regions, and groups characterized by volatility and uncertainty are provided. Via use of exemplary systems and methods, decision makers, for example politicians, warfighters, and analysts can gain insight into the cultures, attitudes, events, and relationships that may impact their missions.

Abstract: An apparatus and method for human activity and facial expression modeling and recognition are based on feature extraction techniques from time sequential images. The human activity modeling includes determining principal components of depth and/or binary shape images of human activities extracted from video clips. Independent Component Analysis (ICA) representations are determined based on the principal components. Features are determined through Linear Discriminant Analysis (LDA) based on the ICA representations. A codebook is determined using vector quantization, Observation symbol sequences in the video clips am determined. And human activities are learned using the Hidden Markov Model (HMM) based on status transition and an observation matrix.

Abstract: A clock-less asynchronous processing circuit or system is configured to operation in a plurality of modes. In an initialization mode (e.g., reset, initialization, boot up), a self-clocked generator associated with the asynchronous circuit is configured to generate an active complete signal (to latch output processed data) within a first period of time after receiving a trigger signal. In a normal mode, the self-clocked generator is configured to generate the active complete signal within a second period of time after receiving the trigger signal. In one embodiment, during the initialization mode, the asynchronous circuit latches the output slower than when in the normal mode.

Abstract: Disclosed are an intelligent illumination control method, apparatus, and system. The method includes a step of obtaining at least one image of a predetermined lighting area captured by at least one stereo camera; a step of determining, based on the at least one image, one or more target illuminance values of the predetermined lighting area; and a step of determining, based on the one or more target illuminance values, a dimming level of at least one illumination apparatus so that the at least one illumination apparatus works according to the determined dimming level.

Abstract: An information processing system separately generates sample sequences from a posterior distribution of each random variable in a probability model representing the structure of a template network that serves as a template for a plurality of networks whose network structures are to be learned, and from a posterior distribution of each random variable in a probability model representing the structures of the plurality of networks, using learning data and hyperparameters relating to the plurality of networks. Next, the information processing system derives a predictive value of the strength of a link specified by an external variable based on the external variable and on the sample sequences.

Abstract: A computer-implemented method for determining a configuration of a plurality of components in a systems installation which satisfies one or more constraints.

Abstract: Implicit parameters and implicit arguments are useful in many programming paradigms including functional and logic programming. Implicit parameter declaration order is inferred from the subroutine parameter usage order in the subroutine body. It means that implicit parameters have limited possibilities to be declared in the same order as programmers want. The parameter ignorance operator # allows changing implicit parameter order, but usage of this operator leads to subroutine declaration syntax similar to the syntax of declaring subroutine parameters explicitly, partially losing syntax benefits gained of implicit parameters. In order to preserve all the benefits of implicit parameter usage and allow programmers to change implicit parameter declaration order and scope in concise way, the Grace˜ operator, which is presented in this document, was invented.

Abstract: Provided are an uplink power control method and device based on a genetic algorithm in a communication network. The method includes: modelling a communication network to obtain a theoretically optimal mobile terminal transmission power expression; determining a fitness function in combination of a genetic algorithm; determining the number of bits of a binary string of a variable; initializing populations; returning an actual value from the binary string to serve as an actual variable; and obtaining the most robust gene and the weakest gene in a chromosome according to the fitness function, designing a genetic operator and determining operating parameters of the genetic algorithm according to the most robust gene and the weakest gene. Using the solution enables a base station to properly indicate to dynamically adjust the uplink transmission power of a home mobile terminal, thereby ensuring excellent system performance of the communication network.

Abstract: A method for sending requests includes: determining, by a device comprising a processor, the requests and Transmission Control Protocol (TCP) connections between a client and a proxy server; and sending, by the device, the requests to the proxy server via idle TCP connections between the client and the proxy server to forward the requests to a Web server by the proxy server, or establishing, by the device, TCP connections between the client and the proxy server depending on whether the requests are serial or parallel requests, the number of the idle TCP connections between the client and the proxy server, and the number of TCP connections which are needed during sending the requests; and sending, by the device, the requests to the proxy server via the idle TCP connections and the established TCP connections to forward the requests to the Web server by the proxy server.

Abstract: A method for processing and verifying remote dynamic data is provided. The method includes providing a radix tree structure having N levels, obtaining and recording N initial values for representing the empty radix tree structure, wherein all nodes at the same level are assigned an identical initial value. When performing a data processing operation to the radix tree structure, determining a first leaf node and calculating and recording the value of each node in a shortest path from the first leaf node to the root node. When performing a verification of a specific data, obtaining a second leaf node corresponding to the specific data, a sibling node of each node in a shortest path from the second leaf node to the root node, and generating a verification result according to a digital signature for verifying the root node, the value of each obtained sibling node, and the specific data.

Abstract: A performance analyzer for a self-tuning system controller, and a method for performance analysis. A range of values for a control parameter of a system controller for a system is split into a plurality of sub-ranges, need is determined to obtain a data point for a sub-range of the plurality of sub-ranges based on a criteria, wherein said sub-range is adjacent to a sub-range having a best performance value that identifies a best performance for the system, the control parameter is set to a value to generate the data point for the adjacent sub-range; and the control parameter set to a value for system performance, based on a search range determined from a window of data points that includes the generated data point.

Abstract: A search device and method of a pertinent solution using a genetic algorithm that performs genetic operation(s) on a plurality of individuals each having an element of a candidate solution to a problem in the form of a gene sequence. Genetic information about target individuals includes whether all individuals are, regardless of their fitness values, in a state among a living state that is a target of genetic operation and a target of calculating a fitness value, and a dead state that is not the target of genetic operation nor the target of the calculation of the fitness value. Each target individual has a predetermined value of a lifespan. A breeding area that allows predation of leading an individual belonging to a lower layer to a dead state due to predation by an individual belonging to a higher layer in the breeding area is an aspect of generating new target individuals.

Abstract: Roughly described, a training database contains N segments of data samples. Candidate individuals identify a testing experience level, a fitness estimate, a rule set, and a testing set TSi of the data samples on which it is tested. The testing sets have fewer than all of the data segments and they are not all the same. Testing involves testing on only the individual's assigned set of data segments, updating the fitness estimates and testing experience levels, and discarding candidates through competition. If an individual reaches a predetermined maturity level of testing experience, then validating involves further testing it on samples of the testing data from a testing data segment other than those in the individual's testing set TSi. Those individuals that satisfy validation criteria are considered for deployment.

Abstract: Data for simulation are selected from an in-memory database of an in-memory database server or simultaneous scenarios simulation at a business application server. The simulation results of a plurality of scenarios received from the business application server are temporarily stored at the in-memory database. One scenario from the plurality of scenarios is selected based on using user-defined rules at the in-memory database server. The selected scenario is communicated to the business application server.

Abstract: The technology described herein includes a system and/or a method for multiple hypothesis tracking. In some examples, a multiple hypothesis tracking system includes a receiver, an array generation module, and a local search move module. The receiver is configured to receive tracking data associated with one or more target families from one or more sensors. The array generation module is configured to generate a matrix array based on the tracking data. The local search move module is configured to perform one or more local search moves on one or more cells in the matrix array to increase a global hypothesis score for the tracking data.

Abstract: The present disclosure describes systems and methods for performing multi-level reservoir history matching. At least some illustrative embodiments include a method that includes generating a first history-matched model using at least one updated model parameter derived from one or more existing model parameters, generating a set of second history-matched models by applying a probabilistic inversion to the first history-matched model, and deriving a set of third history-matched models from the set of second history-matched models. The method further includes generating dynamic simulation realization sets using each of the set of third history-matched models, ranking each of the set of third history-matched models based at least in part on the dynamic simulation realization sets, and presenting a production forecast to a user based on the highest ranked third history-matched models.

Abstract: Determining a system configuration for performing a collective operation on a parallel computer that includes a plurality of compute nodes, the compute nodes coupled for data communications over a data communications network, including: selecting a system configuration on the parallel computer for executing the collective operation; executing the collective operation on the selected system configuration on the parallel computer; determining performance metrics associated with executing the collective operation on the selected system configuration on the parallel computer; selecting, using a simulated annealing algorithm, a plurality of test system configurations on the parallel computer for executing the collective operation, wherein the simulated annealing algorithm specifies a similarity threshold between a plurality of system configurations; executing, the collective operation on each of the test system configurations; and determining performance metrics associated with executing the collective operation o

Abstract: One aspect of the present invention relates to a method for detecting a phishing website. The method includes acquiring information related to a microblog post containing a uniform resource locator (URL) of a website; analyzing the information related to the microblog post to extract features of the microblog post; calculating credibility of the URL of the website contained in the microblog post according to the extracted features of the microblog post; and determining according to the credibility of the URL of the website whether the URL of the website is a URL of a phishing website.

Abstract: A method, a system and a computer program product for selecting a further inquiry for a user to clarify a request for information from the user. One or more candidate answers to the request for information from the user are determined, and a score value is generated for each of one or more characteristics of each candidate answer, where at least one characteristic is associated with an inquiry for the user to clarify the request for information. A characteristic associated with an inquiry is determined that includes score values providing the greatest potential adjustment for the candidate answers in response to a clarification of the request for information, and the inquiry is selected that is associated with the determined characteristic for presentation to the user.

Abstract: There is provided an information processing method including inputting a feature quantity vector and an objective variable corresponding to the feature quantity vector, generating a basis function for outputting a scalar quantity by mapping the feature quantity vector, mapping the feature quantity vector using the basis function and calculating the scalar quantity corresponding to the feature quantity vector, evaluating whether or not the basis function used to calculate the scalar quantity is useful for estimating the objective variable using the objective variable along with the scalar quantity and the feature quantity vector corresponding to the scalar quantity, generating an estimation function for estimating the objective variable from the scalar quantity by machine learning on the basis of the scalar quantity and the objective variable corresponding to the scalar quantity using the basis function evaluated to be useful, and outputting the estimation function.

Abstract: A data handling device has access to a store of existing metadata pertaining to existing documents having associated metadata terms. It analyses the metadata to generate statistical data as to the co-occurrence of pairs of terms in the metadata of one and the same document. When a fresh document is received, it is analysed to assign to it a set of terms and determine for each a measure of their strength of association with the document. Then, for each term of the set, a score is generated that is a monotonically increasing function of (a) the strength of association with the document and of (b) the relative frequency of co-occurrence of that term and another term that occurs in the set; metadata for the fresh document are then selected as the subset of the terms in the set having the highest scores.

Abstract: The techniques discussed herein efficiently perform data-parallel computations on collections of data by implementing a differential dataflow model that performs computations on differences in the collections of data. The techniques discussed herein describe defined operators for use in a data-parallel program that performs the computations on the determined differences between the collections of data by creating a lattice and indexing the differences in the collection of data according to the lattice.

Abstract: A parallel genetic algorithm computing process tracks forward progress of a first sub-population across generations thereof. The first sub-population is one of a plurality of sub-populations that form a population of candidate solutions to an optimization problem. At a current generation of the first sub-population, it is determined that forward progress of the first sub-population fails a set of one or more forward progress criteria. In response to determining that the forward progress of the first sub-population fails the set of one or more forward progress criteria at the current generation, a local catastrophe is invoked on the current generation of the first sub-population. The first sub-population is re-populated after the local catastrophe is invoked. The first sub-population is re-established after re-populating while constraining migration to the first sub-population.

Abstract: Determining a system configuration for performing a collective operation on a parallel computer that includes a plurality of compute nodes, the compute nodes coupled for data communications over a data communications network, including: selecting a system configuration on the parallel computer for executing the collective operation; executing the collective operation on the selected system configuration on the parallel computer; determining performance metrics associated with executing the collective operation on the selected system configuration on the parallel computer; selecting, using a simulated annealing algorithm, a plurality of test system configurations on the parallel computer for executing the collective operation, wherein the simulated annealing algorithm specifies a similarity threshold between a plurality of system configurations; executing, the collective operation on each of the test system configurations; and determining performance metrics associated with executing the collective operation o

Abstract: A model optimization system is configured to determine quality of variables for model generation. A data storage stores input variables, quality metrics for the input variables, and weights for the quality metrics. The quality metrics describe sufficiency of data for the input variables and the data is provided for a plurality of regions. A scoring module determines a score for each region based on the input variables and the weighted quality metrics. An optimizer determines whether at least one of the input variables for a region is to be modified based on the scores, and determines whether the total score for the region is operable to be improved using a modified input variable.

Abstract: A method, system and computer program product for strategy development and resource management for achieving a goal. The goal is divided into a plurality of first-generation sub-goals to form a goal hierarchy. At least one parameter is defined for the first-generation of sub-goals. The sub-goals are further divided into subsequent generations of sub-goals if the number of generations of sub-goals is less than a threshold value. A multi-level concentric representation of the goal hierarchy is created, based on the at least one parameter. The multi-level concentric representation is used for developing a strategy for achieving the goal.

Abstract: Various embodiments provide lossless compression of an enumeration space for genetic founder lines. In one embodiment, an input comprising a set of genetic founder lines and a maximum number of generations G is obtained. A set of genetic crossing templates of a height h is generated. A determination is made if at least a first genetic crossing template in the set of genetic crossing templates is redundant with respect to a second genetic crossing template in the set of genetic crossing templates. Based on the at least first genetic crossing template being redundant is redundant with respect to the second genetic crossing template, the at least first genetic crossing template is removed from the set of genetic crossing templates. This process of removing the at least first genetic crossing template from the set of genetic crossing templates the redundant creates an updated set of genetic crossing templates.

Abstract: Approaches are described for ranking multiple products or other items, such as products obtained in response to a search request submitted to a server. The ranking system determines a ranking score for the products based on both data available online and item data that must be computed offline due to longer computation time or unavailability of data. The ranking score can be used to rank the products and determine which products are the most relevant to the user. A hybrid boosting method is used to first train an online ranking function to produce an online ranking score for the item. In the second phase, an offline ranking function is trained to produce a second ranking score for the item. The online rank score is combined with the offline rank score at query time to produce a combined rank for the items in the search results.

Abstract: Methods, systems and computer program products to measure the adaptability of complex systems, including systems of systems, are disclosed. The methods, systems and computer program products provide rigor and defensibility to the analysis and assessment of adaptability. As a result, systems can be designed or acquired that are intrinsically more adaptable and better able to respond to changing environments.

Abstract: Methods, systems and computer program products to evaluate or assess strategies for operating and designing complex systems, including systems of systems, are disclosed. The methods, systems and computer program products provide describe and evaluate the behavior of systems in real-world environments where future conditions are highly uncertain are disclosed. The present disclosure identifies a set of important strategies, a set of concomitant actions, and a set of environmental conditions that form the basis of strategic change rules. These rules can be incorporated in a simulation to modify the behavior of the simulated system.

Abstract: Methods, systems and computer program products to measure system re-taskability are disclosed. The methods, systems and computer program products may be used in the design of a new or redesign of an existing System of Systems (SoS). Systems re-tasking (aka substitutability or stand-in redundancy) is the process of using different systems to substitute for non-operational systems to meet required functionality, or using multi-function systems to fulfill higher-priority tasks. This ability can increase the overall operational availability of the SoS; it can also increase the adaptability and resilience of the SoS to unknown or changing conditions. The disclosed methods, systems and computer products include simulating an SoS over time, replacing systems that become non-operational (or damaged) with systems that can fulfill the same capability in order to maximize the SoS availability.

Abstract: A method and apparatus for detection of relationships between objects in a meta-model semantic network is described. Semantic objects and semantic relations of a meta-model of business objects are generated from a meta-model semantic network. The semantic relations are based on connections between the semantic objects. A neural network is formed based on usage of the semantic objects and the semantic relations. The neural network is integrated with the semantic objects and the semantic relations to generate a contextual network. A statistical analysis of the connections between the semantic objects in the contextual network is performed to identify stronger semantic relations. The identified stronger semantic relations are used to update the neural network. The updated neural network is integrated into the contextual network.

Abstract: Roughly described, a data mining system includes a candidate gene database in which each candidate individual has a respective fitness estimate. A gene pool processor tests individuals from the candidate gene pool on training data and updates the fitness estimate of the individuals. A gene harvesting module deploys selected individuals from the gene pool. The gene pool processor includes a competition module which selects individuals for discarding in dependence upon their updated fitness estimate. The system maintains a fitness training history for each of the candidate individuals, identifying the data samples on which the individual has been tested. The historical information can be used to assist in any one or more of the following: competition among the individuals, avoiding re-testing of an individual on the same data sample, removing duplicate test data before merging fitness evaluations, improving gene pool diversity, and selecting individuals for deployment.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for normalizing native application scores. In an aspect, a system ranks web resources and native applications based on web resource scores and normalized native application scores that are normalized to the web resource scores. The ranking is indicative of the relevance of each web resource and native application for a search operation relative to each other web resource and native application.

Abstract: A multivariate digital camera device and method for generating pictures of datasets comprised of points in hyperspace is provided. The invention may be embodied in an input device, a computer processor, and an output device. The input device may be a keyboard, a laboratory instrument such as a mass spectrometer, a reader of computer readable medium, or a network interface device. The output device may be a monitor used in conjunction with either a 2D or 3D printer or both. The computer processor receives data from the input device and performs a series of steps to create a 2D or 3D image of the hyperspace object. The resulting image is then produced in a non-transitory medium by at least one of the output devices. The processor steps include the use of a maximum distance method in which distances and angles information from the points in the hyperspace dataset are preserved to produce a more picture-like quality.

Abstract: Disclosure is a multi-objective semiconductor product capacity planning system and method thereof. The system comprises a data input module, a capacity planning module and a computing module. The machine information of the production stations, the product information and the order information are input by the data input module. According to the demand quantity of order, capacity information and product information, the capacity planning module plans a capacity allocation to determine the satisfied quantity of orders. The capacity allocation information is used to form a gene combination by chromosome encoding method. The computing module calculates the gene combination several times to generate numerous candidate solutions by a multi-objective genetic algorithm. The numerous candidate solutions sorts out and generates a new gene combination, and repeats the calculation to form candidate solution set until stop condition is satisfied.

Abstract: Roughly described, a computer-implemented evolutionary data mining system includes a memory storing a candidate gene database in which each candidate individual has a respective fitness estimate; a gene pool processor which tests individuals from the candidate gene pool on training data and updates the fitness estimate associated with the individuals in dependence upon the tests; and a gene harvesting module for deploying selected individuals from the gene pool, wherein the gene pool processor includes a competition module which selects individuals for discarding in dependence upon both their testing experience level and a diversity measure of individuals in the gene pool.

Abstract: A computer-implemented method for processing and/or analyzing nucleic acid sequencing data comprises receiving a first data input and a second data input. The first data input comprises untargeted sequencing data generated from a first nucleic acid sample obtained from a subject. The second data input comprises target-specific sequencing data generated from a second nucleic acid sample obtained from the subject. Next, with the aid of a computer processor, the first data input and the second data input are combined to produce a combined data set. Next, an output derived from the combined data set is generated. The output is indicative of the presence or absence of one or more polymorphisms of the first nucleic acid sample and/or the second nucleic acid sample.

Abstract: A method of constructing an optimized network simulation environment according to the present invention includes the steps of identifying communication equipment models for relaying a message to/from real equipments out of communication equipment models within a network model, as major models, calculating the order of abstraction priority for major models, performing batch-mode abstraction for non-major models, driving a simulation, determining whether a difference between a simulation execution time and an actual time spent is within an allowable delay value, performing adaptive abstraction for the major models, and evaluating a result of the simulation. If the method according to the present invention is used, a real-time simulation having fidelity and reliability for the function and operation of real equipments can be guaranteed.

Abstract: A state (i.e., ket) of a set of qubits may be simulated via a classical computer. Ordering characteristics of the ket (i.e., the “current” permutation associated with the state) may be determined. An operator (which may be associated with a certain operation to perform on the ket) may be defined and simulated. Ordering characteristics of the operator (i.e., the “current” permutation associated with operator) may be determined. If the current permutations of the state and operator match, then the operation may be performed to generate a new ket. Alternatively, the operator may be permuted to match the permutation of the current state. Or the state may be permuted to match the current operator permutation. The operation may then be performed, and the state and permutation remembered for the next operation. The process may be repeated for each operation in the series.

Abstract: Provided is a non-transitory computer readable medium storing a program causing a computer to function as a learning data acquiring unit that acquires learning data, a memory unit that performs machine learning using the learning data about cluster division where Markov chains of transition via a link from a node to a node on a network formed from plural nodes are divided into plural clusters each of which is indicated by a biased Markov chain and calculates a steady state of each biased Markov chain, a search condition receiving unit that receives a search condition from a user, a cluster extracting unit that extracts clusters suitable for the search condition, a partial network cutting unit that cuts a partial network formed by a node group belonging to the clusters, and an importance calculating unit that calculates importance of each node on the partial network.

Abstract: Figures of merit by actual design parameters are tracked over iterations for candidate solutions that include both actual design parameters and actual context parameters. Instead of returning a current iteration figure of merit, a worst observed figure of merit for a set of actual design parameters is returned as the figure of merit for a candidate solution. Since the candidate solution includes both actual design parameters and actual context parameters and the worst observed figures of merit are tracked by actual design parameters, the figure of merit for a set of design parameters will be the worst of the observed worst case scenarios as defined by the actual context parameters over a run of a metaheuristic optimizer.

Abstract: Figures of merit by actual design parameters are tracked over iterations for candidate solutions that include both actual design parameters and actual context parameters. Instead of returning a current iteration figure of merit, a worst observed figure of merit for a set of actual design parameters is returned as the figure of merit for a candidate solution. Since the candidate solution includes both actual design parameters and actual context parameters and the worst observed figures of merit are tracked by actual design parameters, the figure of merit for a set of design parameters wilt be the worst of the observed worst case scenarios as defined by the actual context parameters over a run of a metaheuristic optimizer.

Abstract: The invention involves generating and presenting, typically electronically, a number of design alternatives to persons who are participating in the design, selection, or market research exercise. The participants (referred to as “selectors”) transmit data indicative of their preferences among or between the presented design alternatives, and that data is used to derive a new generation of design alternatives or proposals. The new designs are generated through the use of a computer program exploiting a genetic or evolutionary computational technique. The process is repeated, typically for many iterations or cycles.