A Framework for Spatio-Temporal Data Analysis and Hypothesis Exploration

We present a general framework for pattern discovery and hypothesis exploration in spatio-temporal data sets that is based on delay-embedding. This is a remarkable method of nonlinear time-series analysis that allows the full phase-space behaviour of a system to be reconstructed from only a single observable (accessible variable). Recent extensions to the theory that focus on a probabilistic interpretation extend its scope and allow practical application to noisy, uncertain and high-dimensional systems. The framework uses these extensions to aid alignment of spatio-temporal sub-models (hypotheses) to empirical data - for example satellite images plus remote-sensing - and to explore modifications consistent with this alignment. The novel aspect of the work is a mechanism for linking global and local dynamics using a holistic spatio-temporal feedback loop. An example framework is devised for an urban based application, transit centric developments, and its utility is demonstrated with real data

A local global pattern matching method for subsurface stochastic inverse modeling

Inverse modeling is an essential step for reliable modeling of subsurface flow and transport, which is important for groundwater resource management and aquifer remediation. Multiple-point statistics (MPS) based reservoir modeling algorithms, beyond traditional two-point statistics-based methods, offer an alternative to simulate complex geological features and patterns, conditioning to observed conductivity data. Parameter estimation, within the framework of MPS, for the characterization of conductivity fields using measured dynamic data such as piezometric head data, remains one of the most challenging tasks in geologic modeling. We propose a new local global pattern matching method to integrate dynamic data into geological models. The local pattern is composed of conductivity and head values that are sampled from joint training images comprising of geological models and the corresponding simulated piezometric heads. Subsequently, a global constraint is enforced on the simulated geologic models in order to match the measured head data. The method is sequential in time, and as new piezometric head become available, the training images are updated for the purpose of reducing the computational cost of pattern matching. As a result, the final suite of models preserve the geologic features as well as match the dynamic data. This local global pattern matching method is demonstrated for simulating a two-dimensional, bimodally-distributed heterogeneous conductivity field. The results indicate that the characterization of conductivity as well as flow and transport predictions are improved when the piezometric head data are integrated into the geological modeling. (C) 2015 Elsevier Ltd. All rights reserved.The authors gratefully acknowledge the financial support by DOE through projects DE-FE0004962 and DE-SC0001114. The last author acknowledges the support of the Spanish Ministry of Economy and Competitiveness through project CGL2011-23295. We greatly thank the three anonymous reviewers for their comments, which substantially improved the manuscript.Li ., L.; Srinivasan, S.; Zhou, H.; Gómez Hernández, JJ. (2015). A local global pattern matching method for subsurface stochastic inverse modeling. Environmental Modelling and Software. 70:55-64. https://doi.org/10.1016/j.envsoft.2015.04.008S55647

A framework for promoting interoperability in a global electronic market-space

The primary contributions to the area of electronic business integration, propounded by this thesis, are (in no particular order):  A novel examination of global Business-to-Business (B2B) interoperability in terms of a "multiplicity paradox" and of a "global electronic market-space" from a Complex Systems Science perspective.  A framework for an, integrated, global electronic market-space, which is based on a hierarchical, incremental, minimalist-business-pattern approach. A Web Services-SOA forms the basis of application-to-application integration within the framework. The framework is founded in a comprehensive study of existing technologies, standards and models for secure interoperability and the SOA paradigm. The Complex Systems Science concepts of "predictable structure" and "structural complexity" are used consistently throughout the progressive formulation of the framework.  A model for a global message handler (including a standards-based message-format) which obviates the common problems implicit in standard SOAP-RPC. It is formulated around the "standardized, common, abstract application interface" critical success factor, deduced from examining existing models. The model can be used in any collaboration context.  An open standards-based security model for the global message handler. Conceptually, the framework comprises the following:  An interoperable standardized message format: a standardized SOAP-envelope with standardized attachments (8-bit binary MIME-serialized XOP packages).  An interoperable standardized message-delivery infrastructure encompassing an RPC-invoked message-handler - a Web service, operating in synchronous and/or asynchronous mode, which relays attachments to service endpoints.  A business information processing infrastructure comprised of: a standardized generic minimalist-business-pattern (simple buying/selling), comprising global pre-specifications for business processes (for example, placing an order), standardized specific atomic business activities (e.g. completing an order-form), a standardized document-set (including, e.g. an order-form) based on standardized metadata (common nomenclature and common semantics used in XSD's, e.g. the order-form), the standardized corresponding choreography for atomic activities (e.g. acknowledgement of receipt of order-form) and service endpoints (based on standardized programming interfaces and virtual methods with customized implementations).Theoretical ComputingPHD (INFORMATION SYSTEMS