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The need for efficient monitoring of spatio-temporal dynamics in large environmental applications , such as the water quality monitoring in rivers and lakes, motivates the use of robotic sensors in order to achieve sufficient spatial coverage. Typically, these robots have bounded resources, such as limited battery or limited amounts of time to obtain(More)
When monitoring spatial phenomena, such as the ecological condition of a river, deciding where to make observations is a challenging task. In these settings, a fundamental question is when an active learning, or sequential design, strategy, where locations are selected based on previous measurements, will perform significantly better than sensing at an a(More)
The objectives of this study were to improve understanding of the biochemical mechanisms underlying the growth defects resulting from deletion of pflB and ldhA in E. coli (strain NZN111) and identify genes for which overexpression would relieve this growth defect. Our approach involved the application of a mixed library selection method [Lynch et al., 2007.(More)
A broad range of embedded networked sensor (ENS) systems for critical environmental monitoring applications now require complex, high peak power dissipating sensor devices, as well as on-demand high performance computing and high bandwidth communication. Embedded computing demands for these new platforms include support for computationally intensive image(More)
Many robotic path planning applications, such as search and rescue, involve uncertain environments with complex dynamics that can be only partially observed. When selecting the best subset of observation locations subject to constrained resources (such as limited time or battery capacity) it is an important problem to trade off exploration (gathering(More)
Non-intrusive load monitoring, or energy disaggregation, aims to separate household energy consumption data collected from a single point of measurement into appliance-level consumption data. In recent years, the field has rapidly expanded due to increased interest as national deployments of smart meters have begun in many countries. However, empirically(More)
A descriptive epidemiological study of fungal rhinosinusitis (FRS) was conducted in rural north India in the form of house-to-house survey of villages of two districts each of Punjab and Haryana provinces using a clinical case definition of chronic rhinosinusitis (CRS). The suspected cases were investigated further in the laboratory to confirm FRS. Air and(More)
Inferring human activity is of interest for various ubiquitous computing applications, particularly if it can be done using ambient information that can be collected non intrusively. In this paper, we explore human activity inference, in the context of energy consumption within a home, where we define an "activity" as the usage of an electrical appliance,(More)
Residential buildings contribute significantly to the overall energy consumption across most parts of the world. While smart monitoring and control of appliances can reduce the overall energy consumption, management and cost associated with such systems act as a big hindrance. Prior work has established that detailed feedback in the form of appliance level(More)
One of the primary aspects of sustainable development involves accurate understanding and modeling of environmental phenomena. Many of these phenomena exhibit variations in both space and time and it is imperative to develop a deeper understanding of techniques that can model space-time dynamics accurately. In this paper we propose NOSTILL-GP-NOn-stationary(More)