Mobile cameras as new technologies of surveillance? How citizens experience the use of mobile cameras in public nightscapes.

In Surveillance Studies the terms ‘sousveillance’ and ‘inverse surveillance’ describe forms of surveillance that have a bottom-up and democratic character. However, in this paper this democratic notion is questioned by looking into practices and experiences with both Closed Circuit Television (CCTV) and mobile cameras by Dutch citizens. By intervening in the nightlife district of the\ud Rotterdam1 city centre, data has been gathered on both mobile- and CCTV camera confrontations. From this, an exploration is made into how mobile cameras are experienced in the nightlife landscape. Comparing these experiences with CCTV provides insight into new surveillance issues that emerge due to the mobile camera. The perspective of analyzing surveillance technologies as hybrid collectives that may take different shapes in different places, allows for a contribution that attempts to improve our understanding of the current changes in the surveillance technology landscap

Operational strategies for optimizing grazing when using automatic milking systems in organic dairy production

Successful grazing when using AMS is possible without having to devote a great deal of time to organize and fetch cows every day. However, a careful strategy and good infrastructure, and observation of cow behaviour and pasture are necessary, and the herd has to adapt to the chosen design and routines. In practice, sectional permanent grazing, part-time grazing and structured rotational grazing have been shown to be successful, in terms of allowing outdoor grazing while still maintaining milking frequency and milk yield. In addition, part-time grazing can be combined with either of the other two systems

Is automatic milking acceptable in organic dairy farming? Quantification of sustainability indicators

The objective of this research, was to quantify sustainability indicators of organic dairy farms using Automatic Milking Systems (AMS), and a comparative group of organic dairy farms using conventional milking systems (CMS). Milk yield per cow was higher for AMS farms but did not result in higher net return to management. Nitrogen surplus per ha of available land was higher for AMS farms, Animal health was unaffected by AMS use, as also most milk quality aspects; somatic cell count, clostridium spores and urea. Acid degree value (ADV), measured as free fatty acids (FFA) in the milk, was higher in milk from AMS users. Labour time was decreased by almost 50% for AMS users, to 2.3 min/cow/day. It could be concluded from quantification of selected indicators on economy, environment, cow health, milk quality, and labour time, that the organic dairy farms using AMS, in spite of the substantial decrease in grazing time, show potential for a sustainable development

Refractive index and layer thickness of an adsorbing protein as reporters of monolayer formation

A method is presented for a separate real-time determination of refractive index and layer thickness of an adsorbing thin layer. The changing angular deflections of TE and TM modes in a dedicated planar waveguide structure are measured. A resolution of 0.01 in the refractive index and 0.5 nm in the average thickness is obtained. The method is illustrated with experimental results on the binding of an antibody to the substrate, both in a physisorption and in an immunoreaction. In the latter, results are consistent with an end-on binding of the antibody to the surface

Wavelets-based non-parametric regression : optimal rate in the sup-norm

The model we will study in this paper is a non-parametric regression model on the unit interval [0; 1] with equidistant deterministic grid design. The unknown regression function is assumed to belong to some H?older class with the smoothness parameter > 1 2 . Furthermore the regression function is observed in a Gaussian noise (precise denitions are given in SECTION 2). Ibragimov and Hasminskii [7] have studied a similar kind of model. They considered a more general grid, namely a stochastic grid design, and the class of functions they took was the class of periodic functions on the interval [0; 2?]. Stone [12] obtained optimal rates of convergence where the regression function was assumed to belong to some H?older class of functions. The same kind of model, but with the emphasis on getting the exact constants were studied in Korostelev [8] (for in ] 1 2 ; 1] ) and in Donoho [2] (for > 1 2 ). In both articles the optimal rates where obtained with kernel methods. Our goal in this article is to obtain optimal rates by using wavelet estimators. Recently wavelet estimators were studied in the context of density estimation (cf. Picard and Kerkyacharian [11]) and in estimation the diusion coecient of a diusion process (cf. Genon-Catalot, Laredo and Picard [5]). In Donoho and Johnstone [3] a non-linear wavelet estimator was used for estimating functions with jumps

Asymptotically minimax estimation of a function with jumps

Asymptotically minimax nonparametric estimation of a regression function observed in white Gaussian noise over a bounded interval is considered, with respect to a L 2 -loss function. The unknown function f is assumed to be m times dierentiable except for an unknown, though nite, number of jumps, with piecewise mth derivative bounded in L 2 -norm. An estimator is constructed, attaining the same optimal risk bound, known as Pinsker's constant, as in the case of smooth functions (without jumps)