Spatio-temporal Modelling of Remote-sensing Lake Surface Water Temperature Data

Remote-sensing technology is widely used in environmental monitoring. The coverage and resolution of satellite based data provide scientists with great opportunities to study and understand environmental change. However, the large volume and the missing observations in the remote-sensing data present challenges to statistical analysis. This paper investigates two approaches to the spatio-temporal modelling of remote-sensing lake surface water temperature data. Both methods use the state space framework, but with different parameterizations to reflect different aspects of the problem. The appropriateness of the methods for identifying spatial/temporal patterns in the data is discussed

Functional Principal Component Analysis for Non-stationary Dynamic Time Series

Motivated by a highly dynamic hydrological high-frequency time series, we propose time-varying Functional Principal Component Analysis (FPCA) as a novel approach for the analysis of non-stationary Functional Time Series (FTS) in the frequency domain. Traditional FPCA does not take into account (i) the temporal dependence between the functional observations and (ii) the changes in the covariance/variability structure over time, which could result in inadequate dimension reduction. The novel time-varying FPCA proposed adapts to the changes in the auto-covariance structure and varies smoothly over frequency and time to allow investigation of whether and how the variability structure in an FTS changes over time. Based on the (smooth) time-varying dynamic FPCs, a bootstrap inference procedure is proposed to detect significant changes in the covariance structure over time. Although this time-varying dynamic FPCA can be applied to any dynamic FTS, it has been applied here to study the daily processes of partial pressure of CO2 in a small river catchment in Scotland

Deconstructing Internet QoS with SulksHuman

The construction of rasterization is a natural issue. In this position paper, we validate the improvement of IPv7, demonstrates the appropriate importance of artificial intelligence. We use large-scale communication to validate that replication [8, 1] can be made interactive, linear-time, and collaborative

Spatiotemporal Statistical Downscaling for the Fusion of In-lake and Remote Sensing Data

This paper addresses the problem of fusing data from in-lake monitoring programmes with remote sensing data, through statistical downscaling. A Bayesian hierarchical model is developed, in order to fuse the in-lake and remote sensing data using spatially-varying coefficients. The model is applied to an example dataset of log(chlorophyll-a) data for Lake Erie, one of the Great Lakes of North America

Instructional strategies in the EGRET course: an international graduate forum on becoming a researcher

In today’s knowledge economy, graduate students in the field of Computer Science are increasingly required to develop sophisticated, multi-faceted knowledge of conducting research across multiple contexts and countries. This paper reports the experience of teaching a course to prepare Computer Science graduate students for conducting research in the international community. The course emphasized development of skills critical for a successful research career in computer science, and included construction of knowledge as well as hands-on application of instructional content. The intended learning outcomes included (a) gaining familiarity with research design and methodologies in computer science, (b) preparing and delivering research presentations, (c) reviewing the literature, (d) reading and writing research papers, (e) writing and evaluating research proposals, and (f) networking in the international research community. In this paper, we describe an innovative instructional design that emphasized international collaboration with graduate students from another university on a different continent, namely the Open University in the UK. Our instructional strategies included (a) remote participation of graduate students across universities and countries in real-time, using technologies for synchronous computer mediated communication, (b) incorporation of collaborative activities using online tools scaffolding students’ construction of sophisticated knowledge of key research activities, and (c) providing students with opportunities for hands-on practical application of concepts in collaborative research activities

The Future of Corporate Tax Reform: A Debate

Professor Geier participated in a Lincoln-Douglas style debate, where the debaters were assigned different roles, so the opinions expressed were not necessarily their own. On the first point debated, Professor Geier was assigned to argue: The Affirmative: We Need to Tax Corporationsat the Entity Level. Others argued the negative: The United States Should Repeal the Corporate Income Tax. On the second point debated, Professor Geier argued the negative, that Dividend Exemption Is NOT the Best Method of Corporate/Shareholder Integration, and is in fact the worst method. On the third point, Professor Geier argued in the affirmative, that the corporate tax rate should be lowered to below 35% in a revenue neutral way

Cosmological Parameter Estimation: Method

CMB anisotropy data could put powerful constraints on theories of the evolution of our Universe. Using the observations of the large number of CMB experiments, many studies have put constraints on cosmological parameters assuming different frameworks. Assuming for example inflationary paradigm, one can compute the confidence intervals on the different components of the energy densities, or the age of the Universe, inferred by the current set of CMB observations. The aim of this note is to present some of the available methods to derive the cosmological parameters with their confidence intervals from the CMB data, as well as some practical issues to investigate large number of parameters

The Future of Corporate Tax Reform: A Debate

Professor Geier participated in a Lincoln-Douglas style debate, where the debaters were assigned different roles, so the opinions expressed were not necessarily their own. On the first point debated, Professor Geier was assigned to argue: The Affirmative: We Need to Tax Corporationsat the Entity Level. Others argued the negative: The United States Should Repeal the Corporate Income Tax. On the second point debated, Professor Geier argued the negative, that Dividend Exemption Is NOT the Best Method of Corporate/Shareholder Integration, and is in fact the worst method. On the third point, Professor Geier argued in the affirmative, that the corporate tax rate should be lowered to below 35% in a revenue neutral way

Hierarchical Species Distribution Modelling Across High Dimensional Nested Spatial Scales

We propose a two-stage modelling approach to evaluate how a large suite of environmental metrics available over nested spatial scales shape species distributions. We focus on dragonfly communities, where the data consist of par- tially observed presence records, making identifying the ecological processes driv- ing the true species distribution/occupancy patterns difficult