480 research outputs found

    Inductive Pattern Formation

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    With the extended computational limits of algorithmic recursion, scientific investigation is transitioning away from computationally decidable problems and beginning to address computationally undecidable complexity. The analysis of deductive inference in structure-property models are yielding to the synthesis of inductive inference in process-structure simulations. Process-structure modeling has examined external order parameters of inductive pattern formation, but investigation of the internal order parameters of self-organization have been hampered by the lack of a mathematical formalism with the ability to quantitatively define a specific configuration of points. This investigation addressed this issue of quantitative synthesis. Local space was developed by the Poincare inflation of a set of points to construct neighborhood intersections, defining topological distance and introducing situated Boolean topology as a local replacement for point-set topology. Parallel development of the local semi-metric topological space, the local semi-metric probability space, and the local metric space of a set of points provides a triangulation of connectivity measures to define the quantitative architectural identity of a configuration and structure independent axes of a structural configuration space. The recursive sequence of intersections constructs a probabilistic discrete spacetime model of interacting fields to define the internal order parameters of self-organization, with order parameters external to the configuration modeled by adjusting the morphological parameters of individual neighborhoods and the interplay of excitatory and inhibitory point sets. The evolutionary trajectory of a configuration maps the development of specific hierarchical structure that is emergent from a specific set of initial conditions, with nested boundaries signaling the nonlinear properties of local causative configurations. This exploration of architectural configuration space concluded with initial process-structure-property models of deductive and inductive inference spaces. In the computationally undecidable problem of human niche construction, an adaptive-inductive pattern formation model with predictive control organized the bipartite recursion between an information structure and its physical expression as hierarchical ensembles of artificial neural network-like structures. The union of architectural identity and bipartite recursion generates a predictive structural model of an evolutionary design process, offering an alternative to the limitations of cognitive descriptive modeling. The low computational complexity of these models enable them to be embedded in physical constructions to create the artificial life forms of a real-time autonomously adaptive human habitat

    Rock fractures analysis using Structure from Motion technology: new insight from Digital Outcrop Models

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    Fractures are one of the most important features of the rocks of the upper crust since they strongly influence their physical and chemical behavior and reflect their tectonic history. For this reason, fracture study plays a key role in different branches of the geosciences. Notwithstanding, the quantification of the features and parameters describing fractures could be unsatisfactory using the standard field techniques because they are mainly based on direct-contact methodologies that are affected by errors, as orientation bias and trace censoring, and scarce representativeness, due to the limited possibility of acquiring information of outcrops partially or totally inaccessible. Recently new remote sensing technologies, such as Terrestrial Laser Scanner (TLS) and Digital Photogrammetry (DP), can help to overcome these limitations. Whereas TLS could be very expensive and difficult to use in geological study, DP permits to obtain similar results in an easier way due to cheaper and lighter equipment and more straightforward procedures. Moreover, DP becomes even more useful when combined with Unmanned Aerial Vehicle (UAV) because permits to acquire digital images from positions inaccessible to humans, allowing to analyze geological objects from points of view previously unimaginable. The images acquired from the ground and/or by the UAV can be then processed using different digital algorithms, such as Structure from Motion (SfM), that permit to create 3D model of the studied outcrop. In geosciences, the 3D model representing the surface of the outcrop is often called Digital Outcrop Model (DOM). Despite DOMs can be really useful in different branches of geosciences, their applications are quite well limited because the procedures of their development and sampling/analysis are scarcely analyzed in literature. It is important to highlight that whereas the UAV-based SfM approach is fairly discussed in literature for simple flat areas, is scarcely treated for application to near vertical and not-planar slopes. Moreover, the validity of some procedures of fracture sampling on 3D model, with special regards to the automatic ones, that have been recently presented in literature, is not well treated for real cases of study. The scarce knowledge about these approaches could cause different troubles to the scientific-users: from the application of avoidable time-consuming routine, to the acquisition and interpretation of erroneous data. This research aims to contribute to the scientific knowledge of the use of digital photogrammetry for fractured rock mass analysis, creating and defining new approaches and procedures for the development, analysis and application of DOMs. Here, a workflow for the fracture analysis of steep rocky outcrops and slopes using the 3D DOM is presented. In particular, the following steps are discussed: (i) image acquisition; (ii) development of 3D model; (iii) sampling of DOM; (iv) quantification and parametrization of the 3D measures; (v) application of the 3D quantitative data and parameters to different case of study. Four different cases of study were selected to validate the proposed method: the upper Staffora Valley and Ponte Organasco (Northern Apennines, Italy), Ormea (Ligurian Alps, Italy), and Gallivaggio (Western Alps, Italy) cases of study. However, this methodology could not completely replace the 'direct-contact' field activity, because some information as roughness, infilling and aperture of fractures cannot be measured satisfactory, and because, where possible, field control measures to validate the 3D data are necessary. However, this methodology could be considered as a new necessary procedure for rock-fracture studies because it allows to overcome the inevitable errors of the ground-based traditional methodology and because the DOMs are always available for the analysis, promoting data sharing and comparison, two fundamental principles on which science have and will have to be basedFractures are one of the most important features of the rocks of the upper crust since they strongly influence their physical and chemical behavior and reflect their tectonic history. For this reason, fracture study plays a key role in different branches of the geosciences. Notwithstanding, the quantification of the features and parameters describing fractures could be unsatisfactory using the standard field techniques because they are mainly based on direct-contact methodologies that are affected by errors, as orientation bias and trace censoring, and scarce representativeness, due to the limited possibility of acquiring information of outcrops partially or totally inaccessible. Recently new remote sensing technologies, such as Terrestrial Laser Scanner (TLS) and Digital Photogrammetry (DP), can help to overcome these limitations. Whereas TLS could be very expensive and difficult to use in geological study, DP permits to obtain similar results in an easier way due to cheaper and lighter equipment and more straightforward procedures. Moreover, DP becomes even more useful when combined with Unmanned Aerial Vehicle (UAV) because permits to acquire digital images from positions inaccessible to humans, allowing to analyze geological objects from points of view previously unimaginable. The images acquired from the ground and/or by the UAV can be then processed using different digital algorithms, such as Structure from Motion (SfM), that permit to create 3D model of the studied outcrop. In geosciences, the 3D model representing the surface of the outcrop is often called Digital Outcrop Model (DOM). Despite DOMs can be really useful in different branches of geosciences, their applications are quite well limited because the procedures of their development and sampling/analysis are scarcely analyzed in literature. It is important to highlight that whereas the UAV-based SfM approach is fairly discussed in literature for simple flat areas, is scarcely treated for application to near vertical and not-planar slopes. Moreover, the validity of some procedures of fracture sampling on 3D model, with special regards to the automatic ones, that have been recently presented in literature, is not well treated for real cases of study. The scarce knowledge about these approaches could cause different troubles to the scientific-users: from the application of avoidable time-consuming routine, to the acquisition and interpretation of erroneous data. This research aims to contribute to the scientific knowledge of the use of digital photogrammetry for fractured rock mass analysis, creating and defining new approaches and procedures for the development, analysis and application of DOMs. Here, a workflow for the fracture analysis of steep rocky outcrops and slopes using the 3D DOM is presented. In particular, the following steps are discussed: (i) image acquisition; (ii) development of 3D model; (iii) sampling of DOM; (iv) quantification and parametrization of the 3D measures; (v) application of the 3D quantitative data and parameters to different case of study. Four different cases of study were selected to validate the proposed method: the upper Staffora Valley and Ponte Organasco (Northern Apennines, Italy), Ormea (Ligurian Alps, Italy), and Gallivaggio (Western Alps, Italy) cases of study. However, this methodology could not completely replace the 'direct-contact' field activity, because some information as roughness, infilling and aperture of fractures cannot be measured satisfactory, and because, where possible, field control measures to validate the 3D data are necessary. However, this methodology could be considered as a new necessary procedure for rock-fracture studies because it allows to overcome the inevitable errors of the ground-based traditional methodology and because the DOMs are always available for the analysis, promoting data sharing and comparison, two fundamental principles on which science have and will have to be base

    Data analytics 2016: proceedings of the fifth international conference on data analytics

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