Abstract: This invention is a computerized method which unites multivariate dataset and then performs various operations including data analytics. The set is stored in a “bipartite synthesis matrix” (BSM), e.g., a rectangular matrix with rows of data objects and columns of variable attributes defined by a plurality of partitions. Data objects are linked to one or more attributes within the matrix based on shared correspondences that occur within attribute partitions (each with a numerical range and a characteristic scale). Links within the matrix between data objects and attribute(s) are based on shared correspondences within partitions. The process exploits mode reduction in which shared correspondences of a BSM (or its graph) interrelate data objects by producing an adjacency matrix or its associated graph.

Abstract: This invention is a computerized method which unites a multivariate dataset and then performs various operations, including data analytics. The set is stored in a “bipartite synthesis matrix” (BSM), e.g., a rectangular matrix with rows of data objects and columns of variable attributes, defined by a plurality of partitions (each with a numerical range and a characteristic scale). Links within the matrix between data objects and attribute(s) are based on shared correspondences within partitions. The process exploits mode reduction in which shared correspondences of a BSM (or its graph) interrelate data objects by producing an adjacency matrix or its associated graph. The partition scale is repeatedly and incrementally altered, varying the density of shared correspondences within the data, based on partition number and size; therefore, a fully connected and weighted unipartite network may be established.

Abstract: This invention is a computerized method which unites a multivariate dataset and then performs various operations, including data analytics. The set is stored in a “bipartite synthesis matrix” (BSM), e.g., a rectangular matrix with rows of data objects and columns of variable attributes, defined by a plurality of partitions (each with a numerical range and a characteristic scale). Links within the matrix between data objects and attribute(s) are based on shared correspondences within partitions. The process exploits mode reduction in which shared correspondences of a BSM (or its graph) interrelate data objects by producing an adjacency matrix or its associated graph. The partition scale is repeatedly and incrementally altered, varying the density of shared correspondences within the data, based on partition number and size; therefore, a fully connected and weighted unipartite network may be established.

Abstract: This paperless book is portable and uses removable ROM devices to provide the visual and aural information displayed in the paperless book. The book can be read in a visual mode, as print, or in an aural mode, as the spoken word corresponding to the print, or in both visual and aural modes. The display mode may be conveniently shifted back and forth between visual and aural, for use, for example, by a counter who uses the book in the aural mode while driving and switches to the visual mode while riding on a train. In addition, the visual display may be manipulated affecting the appearance, for use, for example, by persons with reduced visual acuity. Movies also may be viewed using the paperless book. Finally, portions of the text may be enhanced by additional visual images, music or other sounds.

Abstract: A method and apparatus of sampling a body of water in which discrete samples are successively withdrawn from a body of water and analyte is extracted from the respective samples while integrating the analyte which is extracted from successive samples. A filter unit in which male and female fittings may be locked together, and unlocked to allow replacement of filter membranes/screens discs or elements.