Orthogonal ray scheme: a method for processing interference patterns and reconstructing the shape of a test convex mirror

This report is devoted to the processing of the interference pattern of the tested mirror, obtained using the orthogonal ray scheme, where the convex testing surface is illuminated by a collimated beam, which is perpendicular to the optical axis of the surface. The interference pattern is created by two wavefronts, one of which is reflected from the mirror, while the other wavefront bypasses the mirror and travels directly to the detector plane. The result of interference pattern processing is a topography map formed by several tangential profiles. The proposed method is suited for large diameter convex spherical and aspherical mirrors and does not require a priori information of surface under the test, such as the vertex radius of curvature and the conical constant. Theoretical foundation of the data processing method are presented.

ENHANCED APPROACH FOR SOIL CLASSIFICATION USING BOOSTED C5.0 DECISION TREE ALGORITHM

Data mining includes the utilization of erudite data analysis tools to discover previously unidentified, suitable patterns and relationships in enormous data sets. Data mining tools can incorporate statistical models, machine learning methods such as neural networks or decision trees, and mathematical algorithms. As a result data mining comprises of more process. This performs analysis and prediction than collecting and managing data. The main objective of data mining is to identify valid, potentially useful, novel and understandable correlations and patterns in existing data. Finding and analyzing useful patterns in data is known by different names (e.g., knowledge extraction, information discovery, information harvesting, data archaeology, and data pattern processing). The term data mining is basically utilized by statisticians, database researchers, and the business communities.

Pattern Unifies Autism

Autism is a highly heterogeneous condition, genetically and phenotypically. This diversity of causation and presentation has impeded its definition, recognition, assessment, and treatment. Current diagnostic criteria for autism involve two domains, restricted interests and repetitive behavior (RRBs) and social deficits, whose relationship remains unclear. I suggest that the large suite of traits associated with autism can be usefully conceptualized under the single rubric of “pattern,” a term that connects autism with basic brain and cognitive functions and structures its phenotypes within a single theoretical framework. Autism thus involves increases and enhancements to pattern perception, pattern recognition, pattern maintenance, pattern generation, pattern processing, and pattern seeking. RRBs result from increased and imbalanced pattern-related perception and cognition, and social alterations result in part from the usual lack of clear pattern in social interactions, combined with the interference of RRBs with social development. This framework has strong implications for assessment of social and non-social autism-related traits, personalized therapy, and priorities for research.

Encrypted images in “The Prophecies” of Nostradamus

Graphic cipher was first discovered by the author in "The Prophecies" of Nostradamus, and approximate methods for recovering encrypted images have been proposed. The encryption method of Nostradamus is essentially Caesar's cipher, which was adapted to transmit images instead of text. This method could have scientific value in the 16th century, without reference to the meaning of the hidden images, which is currently unclear. Given the rather high complexity of such a cipher (especially for the 16th century), it is possible that these images carry the main substantive content of the texts under consideration. Problems such as improving methods for pattern processing and identifying new images, mathematical criteria for distinguishing encrypted images from spillover pareidolia effects, and interpreting the images in a historical context remain relevant. The search for more adequate methods for recovering encrypted images is a technically creative challenge. The proposed original approach can serve as the beginning of a conceptual shift in the study of the prophecies of Nostradamus – from interpretations of foggy texts to the image recovery and recognition. The obtained results are essential for the history of steganography and shed a fundamentally new light on the work of Nostradamus.

Neuronic Convolution Model_Li-Yun Fu

How to represent spatiotemporal information in an artificial neuron model has been a problem of longstanding interest in artificial intelligence. After a brief review of recent advances, Caianiello’s neuronic convolutional model is extended in this paper for spatiotemporal information representation. The kernel functions that correspond to the convolutional neuron’s receptive field profile can be described by neural wavelets. The convolutional neuron-based multilayer network and its back propagation algorithm are developed to perform spatiotemporal pattern processing. The results provide a natural framework for the discussion of spatiotemporal information representation in an artificial neural network

Neuronic Convolution Model_Li-Yun Fu

How to represent spatiotemporal information in an artificial neuron model has been a problem of longstanding interest in artificial intelligence. After a brief review of recent advances, Caianiello’s neuronic convolutional model is extended in this paper for spatiotemporal information representation. The kernel functions that correspond to the convolutional neuron’s receptive field profile can be described by neural wavelets. The convolutional neuron-based multilayer network and its back propagation algorithm are developed to perform spatiotemporal pattern processing. The results provide a natural framework for the discussion of spatiotemporal information representation in an artificial neural network