Le vie dell'Impero. Le strade coloniali italiane e il loro rapporto con la manualistica del Ventennio

Imperial roads. The Italian colonial routes and their relationship with 1920-40 manuals

Diels-Alder reactions as an efficient route to high purity cyclic polymers

A simple and efficient route for the synthesis of cyclic polymer systems is presented. Linear furan protected α-maleimide-ω-cyclopentadienyl functionalized precursors (poly(methyl methacrylate) and poly(tert-butyl acrylate)) were synthesized via atom transfer radical polymerization (ATRP) and subsequent substitution of the bromine end-group with cyclopentadiene. Upon heating at high dilution, deprotection of the dieneophile occurs followed by an intramolecular Diels–Alder reaction yielding a high purity cyclic product.

Towards condition-invariant sequence-based route recognition

In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountainbiking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

Different kinds of openings of Luhmann's systems theory: A reply to la Cour et al

Various researchers have called for an 'opening up' of Luhmann's systems theory. We take this short paper as an occasion for a critical reflection on the necessity, existence and possibilities of such an opening. We start by pointing out the inherent openness of Luhmann's theory, and, based on this, discuss three kinds of openings: the international opening, the theoretical opening and the empirical opening. With regard to the latter, we distinguish three general options of using Luhmann's theory for empirical research. Copyright © 2007 SAGE.

Commentaries and Responses to "The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis" [Commentaries lead by Anders af Wahlberg; Responses lead by J.C.F. de Winter]

The following discussion is in response to a 2010 article published in the Journal of Safety Research by J.C.F. de Winter and D. Dodou entitled “The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis” (Volume 41, Number 6, pp. 463-470, available on sciencedirect.com). The editors are pleased to provide a forum for this exchange and welcome further comments.

ACE research vignette 008 : acquisitions - a route to new growth opportunities?

This series of research vignettes is aimed at sharing current and interesting research findings from our team and other international Entrepreneurship researchers. In this vignette, Professor Per Davidsson considers some of the dynamics associated with firm growth.

Visual route recognition with a handful of bits

In this paper we use a sequence-based visual localization algorithm to reveal surprising answers to the question, how much visual information is actually needed to conduct effective navigation? The algorithm actively searches for the best local image matches within a sliding window of short route segments or 'sub-routes', and matches sub-routes by searching for coherent sequences of local image matches. In contract to many existing techniques, the technique requires no pre-training or camera parameter calibration. We compare the algorithm's performance to the state-of-the-art FAB-MAP 2.0 algorithm on a 70 km benchmark dataset. Performance matches or exceeds the state of the art feature-based localization technique using images as small as 4 pixels, fields of view reduced by a factor of 250, and pixel bit depths reduced to 2 bits. We present further results demonstrating the system localizing in an office environment with near 100% precision using two 7 bit Lego light sensors, as well as using 16 and 32 pixel images from a motorbike race and a mountain rally car stage. By demonstrating how little image information is required to achieve localization along a route, we hope to stimulate future 'low fidelity' approaches to visual navigation that complement probabilistic feature-based techniques.

SeqSLAM : visual route-based navigation for sunny summer days and stormy winter nights

Learning and then recognizing a route, whether travelled during the day or at night, in clear or inclement weather, and in summer or winter is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual navigation under changing conditions dubbed SeqSLAM. Instead of calculating the single location most likely given a current image, our approach calculates the best candidate matching location within every local navigation sequence. Localization is then achieved by recognizing coherent sequences of these “local best matches”. This approach removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images. The approach is applicable over environment changes that render traditional feature-based techniques ineffective. Using two car-mounted camera datasets we demonstrate the effectiveness of the algorithm and compare it to one of the most successful feature-based SLAM algorithms, FAB-MAP. The perceptual change in the datasets is extreme; repeated traverses through environments during the day and then in the middle of the night, at times separated by months or years and in opposite seasons, and in clear weather and extremely heavy rain. While the feature-based method fails, the sequence-based algorithm is able to match trajectory segments at 100% precision with recall rates of up to 60%.