Wiener Weltausstellung 1873: A ‘Peripheral’ Perspective of the Triester Zeitung

A consideration of the phenomenon of international exhibitions in the political and cultural history of central-European powers as opposed to the models represented by the London and Paris great exhibitions offers relevant insights into this topic. The Exposition organized in Vienna in 1873 – the first in the German language area – should be studied in the light of the strategic urgency which impelled the Habsburg Empire to fashion or redefine a representation of its multinational formation, in the wake of the military defeats it suffered on the French-Piedmont and Prussian fronts. As will become apparent in the later Berlin exhibition of 1879, the Wiener Weltausstellung already makes clear its desire to exhibit the network of global relations in which the central-European Empires were also trying to gain prominence, despite the essential irrelevance of their extra- European colonial enterprise, as compared to British and French imperialist ventures.The essay comprises a critical reassessment of the existing historiographies specifically devoted to the Viennese Exposition (the most significant of which dates to 1989), to be revised in the light of updated interpretive paradigms, and a further analysis which aims at a first systematic taxonomy of the most significant literary and journalistic echoes of this first central-European Weltausstellung. More specifically, the investigation will focus on the hundreds of articles, correspondence and notes which appeared in the Triester Zeitung, the principal newspaper in German in Habsburg Trieste. These textual sources have not as yet received scholarly attention and they make it possible to investigate the reception of the Exhibition within the geographical and cultural context of the multilingual and multicultural port of Trieste which, despite its peripheral position, was, nonetheless, of primary strategic importance to the central Austrian government

Seasonal availability and physical and chemical characteristics of four major browse plants used for stall-feeding of livestock in Eastern Nigeria

Four major browse species were studied with respect to their time of availability throughout the year and some aspects of their physical and chemical characteristics. Elaeis guineensis and Ficus elasticoides were available at all times of the year for stock feeding. For the physical milling characteristics studied, the browse species compared well with those of the legume species included in the study or were intermediate between those of the legumes and grasses. The nutrient composition indicated that the browse species could be a good source of livestock feed, especially during the dry season when grass from the natural grassland is scarce.Key words: Nutrient composition, milling characteristics, livestock, browse species

1 Indirect estimation of signal-dependent noise with non-adaptive heterogeneous samples

Abstract—We consider the estimation of signal-dependent noise from a single image. Unlike conventional algorithms that build a scatterplot of local mean-variance pairs from either small or adaptively selected homogeneous data samples, our proposed approach relies on arbitrarily large patches of heterogeneous data extracted at random from the image. We demonstrate the feasibility of our approach through an extensive theoretical analysis based on mixture of Gaussian distributions. A prototype algorithm is also developed in order to validate the approach on simulated data as well as on real camera raw images. Index Terms—Noise estimation, signal-dependent noise, Poisson noise

Robust Multi-Image HDR Reconstruction for the Modulo Camera

Photographing scenes with high dynamic range (HDR) poses great challenges to consumer cameras with their limited sensor bit depth. To address this, Zhao et al. recently proposed a novel sensor concept - the modulo camera - which captures the least significant bits of the recorded scene instead of going into saturation. Similar to conventional pipelines, HDR images can be reconstructed from multiple exposures, but significantly fewer images are needed than with a typical saturating sensor. While the concept is appealing, we show that the original reconstruction approach assumes noise-free measurements and quickly breaks down otherwise. To address this, we propose a novel reconstruction algorithm that is robust to image noise and produces significantly fewer artifacts. We theoretically analyze correctness as well as limitations, and show that our approach significantly outperforms the baseline on real data.Comment: to appear at the 39th German Conference on Pattern Recognition (GCPR) 201

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2014 (preprint) 1 Joint Removal of Random and Fixed-Pattern Noise through Spatiotemporal Video Filtering

Abstract—We propose a framework for the denoising of videos jointly corrupted by spatially correlated (i.e. non-white) random noise and spatially correlated fixed-pattern noise. Our approach is based on motion-compensated 3-D spatiotemporal volumes, i.e. a sequence of 2-D square patches extracted along the motion trajectories of the noisy video. First, the spatial and temporal correlations within each volume are leveraged to sparsify the data in 3-D spatiotemporal transform domain, and then the coefficients of the 3-D volume spectrum are shrunk using an adaptive 3-D threshold array. Such array depends on the particular motion trajectory of the volume, the individual power spectral densities of the random and fixed-pattern noise, and also the noise variances which are adaptively estimated in transform domain. Experimental results on both synthetically corrupted data and real infrared videos demonstrate a superior suppression of the random and fixed-pattern noise from both an objective and a subjective point of view. Index Terms—Video denoising, spatiotemporal filtering, fixedpattern noise, power spectral density, adaptive transforms, thermal imaging. I

Modeling Camera Effects to Improve Visual Learning from Synthetic Data

Recent work has focused on generating synthetic imagery to increase the size and variability of training data for learning visual tasks in urban scenes. This includes increasing the occurrence of occlusions or varying environmental and weather effects. However, few have addressed modeling variation in the sensor domain. Sensor effects can degrade real images, limiting generalizability of network performance on visual tasks trained on synthetic data and tested in real environments. This paper proposes an efficient, automatic, physically-based augmentation pipeline to vary sensor effects --chromatic aberration, blur, exposure, noise, and color cast-- for synthetic imagery. In particular, this paper illustrates that augmenting synthetic training datasets with the proposed pipeline reduces the domain gap between synthetic and real domains for the task of object detection in urban driving scenes

Improved Sparse Signal Recovery via Adaptive Correlated Noise Model

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Diventare Claudio Magris: come un germanista scopre il suo meridiano letterario

Il contributo mette in luce alcuni aspetti \u2018letterari\u2019 e stilistici nel 'Mito absburgico' di Claudio Magris, (aggettivazione ossimorica, uso della citazione, genesi del testo), individua quindi l\u2019operazione poetologica per cui attraverso la figura di Scipio Slataper il germanista si costruisce il suo non luogo di saggista-scrittore, e si conclude con alcune osservazioni sul crescente disimpegno dell'autore da una scrittura accademica a favore dell\u2019invenzione dell\u2019io narrante narratore-filologo di 'Danubio' che ormai si auto-redime dalla dannazione bibliografica

Appennino: A GIS Tool for Analyzing Wildlife Habitat Use

The aim of the study was to test Appennino, a tool used to evaluate the habitats of animals through compositional analysis. This free tool calculates an animal's habitat use within the GIS platform for ArcGIS and saves and exports the results of the comparative land uses to other statistical software. Visual Basic for Application programming language was employed to prepare the ESRI ArcGIS 9.x utility. The tool was tested on a dataset of 546 pheasant positions obtained from a study carried out in Tuscany (Italy). The tool automatically gave the same results as the results obtained by calculating the surfaces in ESRI ArcGIS, exporting the data from the ArcGIS, then using a commercial spreadsheet and/or statistical software to calculate the animal's habitat use with a considerable reduction in time