Who are Taxable?—Basic Problems in Definition Under the Illinois Retailers’ Occupation Tax Act

Identification of non-linear systems is a challenge, due to the richness of both model structures and estimation approaches. As a case study, in this paper we test a number of methods on a data set collected from an electrical circuit at the Free University of Brussels. These methods are based on black box and grey box model structures or on a mixture of them, which are all implemented in a forthcoming Matlab toolbox. The results of this case study illustrate the importance of the use of custom (user defined) regressors in a black box model. Based on physical knowledge or on insights gained through experience, such custom regressors allow to build efficient models with a relatively simple model structure.

Overview of methods to analyse dynamic data

This book gives an overview of existing data analysis methods to analyse the dynamic data obtained from full scale testing, with their advantages and drawbacks. The overview of full scale testing and dynamic data analysis is limited to energy performance characterization of either building components or whole buildings. The methods range from averaging and regression methods to dynamic approaches based on system identification techniques. These methods are discussed in relation to their application in following in situ measurements: -measurement of thermal transmittance of building components based on heat flux meters; -measurement of thermal and solar transmittance of building components tested in outdoor calorimetric test cells; -measurement of heat transfer coefficient and solar aperture of whole buildings based on co-heating or transient heating tests; -characterisation of the energy performance of whole buildings based on energy use monitoring

Identification of gravity waves in hydrodynamical simulations

The excitation of internal gravity waves by an entropy bubble oscillating in an isothermal atmosphere is investigated using direct two-dimensional numerical simulations. The oscillation field is measured by a projection of the simulated velocity field onto the anelastic solutions of the linear eigenvalue problem for the perturbations. This facilitates a quantitative study of both the spectrum and the amplitudes of excited g-modes.Comment: 12 pages, 11 figures, Appendices only available onlin

What is the true nature of blinkers?

Aims. The aim of this work is to identify the true nature of the transient EUV brightenings, called blinkers. Methods. Co-spatial and co-temporal multi-instrument data, including imaging (EUVI/STEREO, XRT and SOT/Hinode), spectroscopic (CDS/SoHO and EIS/Hinode) and magnetogram (SOT/Hinode) data, of an isolated equatorial coronal hole were used. An automatic program for identifying transient brightenings in CDS O v 629 Å, EUVI 171 Å and XRT was applied. Results. We identified 28 blinker groups in the CDS O v 629 Å raster images. All CDS O v 629 Å blinkers showed counterparts in EUVI 171 Å and 304 Å images. We classified these blinkers into two categories, one associated with coronal counterparts and other with no coronal counterparts as seen in XRT images and EIS Fe xii 195.12 Å raster images. Around two-thirds of the blinkers show coronal counterparts and correspond to various events like EUV/X-ray jets, brightenings in coronal bright points or foot-point brightenings of larger loops. These brightenings occur repetitively and have a lifetime of around 40 min at transition region temperatures. The remaining blinker groups with no coronal counterpart in XRT and EIS Fe xii 195.12 Å appear as point-like brightenings and have chromospheric/transition region origin. They take place only once and have a lifetime of around 20 min. In general, lifetimes of blinkers are different at different wavelengths, i.e. different temperatures, decreasing from the chromosphere to the corona. Conclusions. This work shows that the term blinker covers a range of phenomena. Blinkers are the EUV response of various transient events originating at coronal, transition region and chromospheric heights. Hence, events associated with blinkers contribute to the formation and maintenance of the temperature gradient in the transition region and the corona

Data-driven Soft Sensors in the Process Industry

In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control. This paper discusses characteristics of the process industry data which are critical for the development of data-driven Soft Sensors. These characteristics are common to a large number of process industry fields, like the chemical industry, bioprocess industry, steel industry, etc. The focus of this work is put on the data-driven Soft Sensors because of their growing popularity, already demonstrated usefulness and huge, though yet not completely realised, potential. A comprehensive selection of case studies covering the three most important Soft Sensor application fields, a general introduction to the most popular Soft Sensor modelling techniques as well as a discussion of some open issues in the Soft Sensor development and maintenance and their possible solutions are the main contributions of this work