Abstract: A computerized method of representing a dataset with a taxonomy includes obtaining a dataset containing a plurality of records; initializing a folder-set containing a plurality of folders; assigning labels to folders within the folder set; and classifying the plurality of records into the plurality of folders according to a predetermined entropic similarity condition.

Abstract: A hierarchy of computing modules is configured to learn a cause of input data sensed over space and time, and is further configured to determine a cause of novel sensed input data dependent on the learned cause. Further, the hierarchy has a first level of computing modules and a second level of at least one computing module, where at least one of the computing modules in the first level is configured to receive a portion of the novel sensed input data, and where the computing module in the first level is further capable of determining a possible cause of the novel sensed input data dependent on analyzing only a subset of the portion of the novel sensed input data.

Abstract: A hierarchy of computing modules is configured to learn a cause of input data sensed over space and time, and is further configured to determine a cause of novel sensed input data dependent on the learned cause. At least one of the computing modules has a sequence learner module configured to associate sequences of input data received by the computing module to a set of causes previously learned in the hierarchy.

Abstract: A configuration that minimizes cost subject to the constraints is selected. A Simple Genetic Algorithm (SGA) is modified to incorporate the handling of constraints. The SGA is further modified to incorporate Optimal-Storage-Profiling to produce an increased number of fit individuals in each generation, developing a policy which will consider configurations of all storage-consumption levels and favor those configurations whose storage-consumption indicate they more likely to be strong candidates. An ideal-distribution of configurations, based on their storage-consumption, for each generation is developed. Different elitist policies are also incorporated to achieve greater scalability without sacrificing the quality of the solution.

Abstract: A method, apparatus and computer-program product for performing a system analysis of a system is disclosed.

Abstract: A hierarchy of computing modules is configured to learn a cause of input data sensed over space and time, and is further configured to determine a cause of novel sensed input data dependent on the learned cause. The hierarchy is further configured to associate a first pattern in the input data and a second pattern in the input data to a same possible cause of the input data.

Abstract: Methods of creating and using robust neural network ensembles are disclosed. Some embodiments take the form of computer-based methods that comprise receiving a set of available inputs; receiving training data; training at least one neural network for each of at least two different subsets of the set of available inputs; and providing at least two trained neural networks having different subsets of the available inputs as components of a neural network ensemble configured to transform the available inputs into at least one output. The neural network ensemble may be applied as a log synthesis method that comprises: receiving a set of downhole logs; applying a first subset of downhole logs to a first neural network to obtain an estimated log; applying a second, different subset of the downhole logs to a second neural network to obtain an estimated log; and combining the estimated logs to obtain a synthetic log.

Abstract: A system and method for generating and validating a user profile (25) for a user based on a static profile (10) and a dynamic profile (15) of the user. The method and system compresses the dynamic rules (15) into aggregated rules so that the user can view a comparatively small number of the aggregated rules and select the desired rules from the aggregated rules based on user desired criteria. The method and system validates user rules (60) using a processing device, which are retrieved from a storage device. The user rules are separated into at least one subset of a user set. Then, it is determined if a particular rule of the at least one subset is one of acceptable, unacceptable and undecided based on a defined criteria (415). If the particular rules of the at least one subset are acceptable, the particular rules of the at least one subset are provided (e.g. assigned) to a corresponding user (435).

Abstract: A hereditary model illustrates a method devised to extrapolate a series of locations of probable progeny earthquake events based on previous “seed” earthquakes. Shadow Zone border P-rings are claimed as precursors to possible future earthquake event locations. The intersection of these P-rings with tectonic plate edges or major fault lines indicates future seismic event targets. The earth physics that underlie the behavior of this forecast method involves the interaction of the refracted P-waves with internal earth processes.

Abstract: A computing apparatus includes a display to present human-readable information and a user input facility. A rule data store contains a statement of rules governing prescribed aspects of presenting data upon the display. These aspects include those aspects subject to variation by language whenever the following changes: type of data, and/or nature of user-operation being performed involving the data. A rules engine is configured to implement the rules. One or more common programs are configured to recognize conditions for applying the rules, and in response, to invoke the rules engine.

Abstract: Logging systems and methods are disclosed to reduce usage of radioisotopic sources. Some embodiments comprise collecting at least one output log of a training well bore from measurements with a radioisotopic source; collecting at least one input log of the training well bore from measurements by a non-radioisotopic logging tool; training a neural network to predict the output log from the at least one input log; collecting at least one input log of a development well bore from measurements by the non-radioisotopic logging tool; and processing the at least one input log of the development well bore to synthesize at least one output log of the development well bore. The output logs may include formation density and neutron porosity logs.

Abstract: The present invention is directed to a computer-based intelligent adviser having particular applicability in industry situations and job positions in which analytical skills are secondary to a position but in which analytical skills are important to achieving the highest level of performance in the business. The present invention contemplates both the process of developing a computer based intelligent adviser as well as a system and process of using a computer-based intelligent adviser.

Abstract: A method is provided for a control system. The method may include obtaining data records associated one or more input variables and one or more output parameters, and selecting one or more input parameters from the one or more input variables. The method may also include generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records, and determining desired respective statistical distributions of the one or more input parameters of the computational model.

Abstract: A computerized system and method for large scale semi-supervised learning is provided. The training set comprises a mix of labeled and unlabeled examples. Linear classifiers based on support vector machine principles are built using these examples. One embodiment uses a fast design of a linear transductive support vector machine using multiple switching. In another embodiment, mean field annealing is used to form a very effective semi-supervised support vector machine. For both these embodiments the finite Newton method is used as the base method for achieving fast training.

Abstract: Method, device and computer program product for support of maintaining a system. The method includes: evaluating a current system state and detecting a first lattice element corresponding to the current system state; locating at least one state improvement path, within a lattice that represents states of the system, between the first lattice element and a second lattice element representative of a target system state; determining, for at least one state improvement path, rules that should be satisfied in order to reach the system target state; and determining how to fulfill the rules associated with at least one state improvement path.

Abstract: An information processing apparatus, capable of identifying vital sign information. A learning unit identifies an emotion/state of the user by comparing the generated feature vectors with feature vectors accumulated in a storage unit. Information indicating the resultant identified emotion/state of the user is output to an output unit via an output controller.

Abstract: Each individual classifier is based on the partial view of the data that is locally available. For the decision made by the classifiers to be consistent, the data sets available to the classifiers are sampled from the same (fixed though unknown) distribution. A test pattern is assumed to be observable across the classifiers. A combined classification is achieved based upon the posterior probabilities computed by, the individual classifiers. The posterior is computed for a test sample based on the posteriors provided by a subset of consistent classifiers.

Abstract: System and method for controlling a process with spatially dependent conditions for producing a product with spatially dependent properties, e.g., a web/sheet-based process for producing a web/sheet-based product. Input data comprising a plurality of input data sets are provided to a neural network (analog or computer-based), each data set comprising values for one or more input parameters, each comprising a respective process condition or product property. The input data preserve spatial relationships of the input data. The neural network generates output data in accordance with the input data, the output data comprising a plurality of output data sets, each comprising values for one or more output parameters, each comprising a predicted process condition or product property. The output data preserve spatial relationships of the output data, which correspond to the spatial relationships of the input data. The output data are useable by a controller or operator to control the process.

Abstract: A method and apparatus improves the block allocation time in a parallel computer system. A pre-load controller pre-loads blocks of hardware in a supercomputer cluster in anticipation of demand from a user application. In the preferred embodiments the pre-load controller determines when to pre-load the compute nodes and the block size to allocate the nodes based on pre-set parameters and previous use of the computer system. Further, in preferred embodiments each block of compute nodes in the parallel computer system has a stored hardware status to indicate whether the block is being pre-loaded, or already has been pre-loaded. In preferred embodiments, the hardware status is stored in a database connected to the computer's control system. In other embodiments, the compute nodes are remote computers in a distributed computer system.

Abstract: A networked interactive expert system is disclosed for selectively providing relevant expertise when a user requires such assistance. System provides a set of networked facilities for determining an expertise needed by a customer based on a location. Such location can be either physical or logical. A physical “location” corresponds, for example, to a department within a retail outlet. Examples of logical “locations” are ones corresponding to a web-page, a product identification code of interest, a customer identification code, and/or explicit knowledge category selected by the customer. An expert studio, from a list of expert studios providing expertise corresponding to the identified location associated with the customer's request, is matched up with the request. Thereafter, a primary connection, supporting an interactive videoconference session, is established between a first networked node associated with the customer and a second networked node associated with the designated expert studio.