We consider the inverse problem of discovering the location of a source from very sparse point measurements in a bounded domain that contains impenetrable (and possibly unknown) obstacles. We present an adaptive algorithm for determining the measurement locations, and ultimately, the source locations. Specifically, we investigate source discovery for the Laplace operator, though the approach ca...

We consider the inverse problem of discovering the location of a source from very sparse point measurements in a bounded domain that contains impenetrable (and possibly unknown) obstacles. We present an adaptive algorithm for determining the measurement locations, and ultimately, the source locations. Specifically, we investigate source discovery for the Laplace operator, though the approach ca...

Copyright © 2006, Idea Group Inc., distributing in print or electronic forms without written permission of IGI is prohibited. INTRODUCTION A very large percentage of business and academic data is stored in textual format. With the exception of metadata, such as author, date, title and publisher, these data are not overtly structured like the standard, mainly numerical, data in relational databa...

Predictive models are widely used in domains ranging from judiciary and healthcare to autonomous driving. As we increasingly rely on these models for high-stakes decisions, identifying and characterizing their unexpected failures in the real world is critical. We categorize errors of a predictive model as: known unknowns and unknown unknowns [3]. Known unknowns are those data points for which t...

Understanding the dynamics by which urban areas attract visitors is important in today’s cities that are continuously increasing population towards higher densities. Identifying services relate to highly attractive districts useful make policies regarding placement of such places. Thus, we present a framework for classifying their attractiveness daily commuters and relating Points Interests (PO...

Univariate calibration method is a simple, cheap and easy to use procedure in analytical chemistry. A univariate analysis will be successful if a selective signal can be found for the analyte(s). In this work, two simple ways were used to find the selective signals, spectral ratio plot (SRP) and loading plot (LP). Both of them were able to discover the selective regions in the recorded data set...

Cities grow in a bottom-up manner, leading to fractal-like urban morphologies characterized by scaling laws. The correlated percolation model has succeeded modeling geometries imposing strong spatial correlations; however, the origin of underlying mechanisms behind spatially growth remains largely unknown. Our understanding human movements recently been revolutionized thanks increasing availabi...