Gaussian Process priors with uncertain inputs? Application to multiple-step ahead time series forecasting

We consider the problem of multi-step ahead prediction in time series analysis using the non-parametric Gaussian process model. k-step ahead forecasting of a discrete-time non-linear dynamic system can be performed by doing repeated one-step ahead predictions. For a state-space model of the form y t = f(Yt-1 ,..., Yt-L ), the prediction of y at time t + k is based on the point estimates of the previous outputs. In this paper, we show how, using an analytical Gaussian approximation, we can formally incorporate the uncertainty about intermediate regressor values, thus updating the uncertainty on the current prediction

The heat of dissociation of the electron pair in liquid ammonia at -33°C

Thesis (M.A.)--Boston UniversityPrevious studies (1) of the anomalous solutions formed by the alkali and alkaline earth metals in liquid ammonia clearly reveal that the various similar properties common to these solutions of a metal dissolved in a non-metal are due to the presence of a common negativ species, some form or "solvated" state of the electron, and are independent of the kind of metal present. The more important characteristic physical properties exhibited by these interesting metal-ammonia solutions are their common color, very high conductivity (2), anomalous volume expansion upon mixing (3), unique magnetic susceptibility (4), and similar thermochemical reactions (5) [TRUNCATED

Derivation of rainfall thresholds for pluvial flood risk warning in urbanised areas

In the recent past throughout the Mediterranean area, many extreme events such as floods, debris flows and landslides occurred. Mediterranean ephemeral streams have specific features compared to other river systems; their basins are small and highly torrential and may generate flash-floods (Camarasa-Belmonte & Soriano-Garcia, 2012). Moreover, the rapid transformation processes of urban areas induced the increase of catchment imperviousness and the derived increase of surface runoff generated during rainfall events. However, flooding events in urban areas occur quite frequently as a consequence of rain events of lower intensity than the design one, even in case of correct network dimensioning. The use of a reliable flood forecasting model in urban areas can play an important role in managing land and water resources. The purpose of this work is the development of a Decision Support System (DSS) for flash flood warning in an urban area. Usually, flood warning systems are based on on-line hydrological and/or hydraulic models in order to provide forecasts of water stages or discharges at critical river sections (Martina et al., 2006; Diakakis, 2012; Wu et al., 2015). This procedure is inappropriate for flash flood warning in urban areas or in catchments with a small area. According to the approach proposed by [Amadio et al., 2003; Wu et al., 2015], in this study the rainfall threshold has been estimated in an urban area by coupling results of hydro-dynamic model in terms of water stage and flooding area. Particularly, dependency of the antecedent soil moisture conditions has been neglected because urban areas are characterized by imperious surfaces This study proposes a methodology to point out in urban areas rainfall thresholds used in flash flood warning which should be influenced by the uncertainties in the rainfall characteristics, including rainfall duration, depth and storm pattern. Particularly, the methodology here developed has a modular structure consisting of different modules: synthetic hyetographs definition to gain the hydrological input to the hydraulic model; transformation of flood discharge to inundated area through a two-dimensional hydraulic model the FLURB-2D model (Aronica & Lanza, 2005) and, finally, quantification of threshold rainfall associated with specific inundation criteria

Rainfall thresholds derivation for warning pluvial flooding risk in urbanised areas

Aim of this work is the development of an operational tool for pluvial flooding warning in an urban area based on off-line rainfall thresholds derived by coupling a rainfall-runoff modelling and a hydraulic routing. The critical conditions considered for issue flood warnings were not only based on the water stage, but also on the extension of the flooded area. Further, a risk assessment framework for quantifying the reliability of the rainfall thresholds has been included; rainfall thresholds used in pluvial flooding warning should be influenced by the uncertainties in the rainfall characteristics (i.e. rainfall duration, depth and storm pattern). This risk assessment framework incorporates the correlated multivariate Monte Carlo simulation method, an hydraulic model for the simulation of rainfall excess propagation over surface urban drainage structures, i.e. streets and pathways. Thresholds rainfall are defined using a number of inundation criteria, to analyze the change in the rainfall threshold due to various definitions of inundation. Starting from estimated water stages and flooded area from inundation simulation rainfall thresholds can be obtained according a specific inundation criterion, including, together, a critical water depth and a critical flooding area. Finally, the second phase concerns the imminence of a possible hydrological risk by comparing the time when cumulative rainfall and rainfall thresholds meet to each other. The developed procedure has been applied to the real case study of Mondello catchment in Palermo (Italy)

Methodology for the Industry Estimates in the 2007 R&D Satellite Account

This paper is part of a series that provides the details behind the Bureau of Economic Analysis's (BEA) satellite account on research and development (R&D) activity. It describes the data and experimental methodology used to create the GDP-by-Industry component of the satellite account for thirteen R&D-intensive industries and an aggregation of all other for-profit industries.