IT tools and standards supporting mass customisation in the building industry

Research demonstrate that productivity in the Danish building and construction industry has only doubled over the last fifty years, whereas the manufacturing industry has increased six times. Utilisation of mass customization as a strategy has achieved results in the manufacturing industry in terms of increasing productivity and competitiveness, so the strategy might have potentials in the building and construction industry as well. However, mass customization as a strategy for improving the productivity of the building and construction industry has not been explored as much as in the manufacturing industry. The purpose of this paper is to analyse the assumptions and possibilities for applying the principles of mass customisation related to establishing an adaptable integrated system of entities in the value chain of the building and construction industry. The outset of the paper is a literature review concerning the utilisation of mass customization as a strategy in terms of increasing productivity within the building and construction industry. An essential part of the paper is a case study of 11 building and construction companies and an analysis of the conditions for cooperation between the entities in the value chain of the building and construction industry. The paper induces to which extent it makes sense to talk about utilisation of mass customisation by applying the Industry Foundation Classes (IFC) and standardisation initiatives of the construction industry provided by buildingSMART, and at the same time harvesting the benefits of the mass customization

Inference of α\alpha-particle density profiles from ITER collective Thomson scattering

The primary purpose of the collective Thomson scattering (CTS) diagnostic at ITER is to measure the properties of fast-ion populations, in particular those of fusion-born $\alpha$-particles. Based on the present design of the diagnostic, we compute and fit synthetic CTS spectra for the ITER baseline plasma scenario, including the effects of noise, refraction, multiple fast-ion populations, and uncertainties on nuisance parameters. As part of this, we developed a model for CTS that incorporates spatial effects of frequency-dependent refraction. While such effects will distort the measured ITER CTS spectra, we demonstrate that the true $\alpha$-particle densities can nevertheless be recovered to within ~10% from noisy synthetic spectra, using existing fitting methods that do not take these spatial effects into account. Under realistic operating conditions, we thus find the predicted performance of the ITER CTS system to be consistent with the ITER measurement requirements of a 20% accuracy on inferred $\alpha$-particle density profiles at 100 ms time resolution.Comment: 17 pages, 11 figures. Accepted for publication in Nucl. Fusio

The tmRDB and SRPDB resources

Maintained at the University of Texas Health Science Center at Tyler, Texas, the tmRNA database (tmRDB) is accessible at the URL with mirror sites located at Auburn University, Auburn, Alabama () and the Royal Veterinary and Agricultural University, Denmark (). The signal recognition particle database (SRPDB) at is mirrored at and the University of Goteborg (). The databases assist in investigations of the tmRNP (a ribonucleoprotein complex which liberates stalled bacterial ribosomes) and the SRP (a particle which recognizes signal sequences and directs secretory proteins to cell membranes). The curated tmRNA and SRP RNA alignments consider base pairs supported by comparative sequence analysis. Also shown are alignments of the tmRNA-associated proteins SmpB, ribosomal protein S1, alanyl-tRNA synthetase and Elongation Factor Tu, as well as the SRP proteins SRP9, SRP14, SRP19, SRP21, SRP54 (Ffh), SRP68, SRP72, cpSRP43, Flhf, SRP receptor (alpha) and SRP receptor (beta). All alignments can be easily examined using a new exploratory browser. The databases provide links to high-resolution structures and serve as depositories for structures obtained by molecular modeling