Analysis and evaluation of a general camera model

A versatile General Camera Model, GCM, has been developed, and is described in detail. The model is general in the sense that it can capture both fisheye and conventional as well as catadioptric cameras in a unified framework. The camera model includes efficient handling of non-central cameras as well as compensations for decentring distortion. A novel way of analysing radial distortion functions of camera models leads to a straightforward improvement of conventional models with respect to generality, accuracy and simplicity. Different camera models are experimentally compared for two cameras with conventional and fisheye lenses, and the results show that the overall performance is favourable for the GCM.     

“This is the size of one meter”: Children’s bodily-material collaboration

In CSCL studies, language is often foregrounded as the primary resource for engaging in collaborative learning, while the body is more often positioned as a secondary resource. There is, however, a growing interest in the body as a resource in learning and collaboration in and outside CSCL. In this paper, we present, analyse, and discuss how two nine-year-old children collaborate through gesturing and moving their bodies around a touchscreen. The pair is working with the concept of scale and area measurement and are in midst of copying their rooms from paper to touchscreen. During this process, the pair engages in a discussion regarding the size of one meter through language, gestures and manipulation of the material resources. The analysis shows two distinct ways of understanding the length of one meter, which primarily are visible through the children’s gestures and bodily movements. In the analysis we show how the children dynamically produce body-material resources for communicative and illustrative purposes; moreover, they use body-material resources as a cognitive tool and as a way of shepherding each other. The study forms part of a body of studies analysing and theorizing the body in education, learning, and interaction. We discuss the wider impact of our findings and argue how they may challenge and improve studies relying mainly on a coding and counting approach or automated capture of e.g. gestures. In addition, we provide a detailed multimodal representation of the subtle bodily-material resources, which we argue is a modest contribution to a catalogue of ways of representing and making bodily-material resources visible in CSCL research.     

Sparse decomposition and modeling of anatomical shape variation

Recent advances in statistics have spawned powerful methods for regression and data decomposition that promote sparsity, a property that facilitates interpretation of the results. Sparse models use a small subset of the available variables and may perform as well or better than their full counterparts if constructed carefully. In most medical applications, models are required to have both good statistical performance and a relevant clinical interpretation to be of value. Morphometry of the corpus callosum is one illustrative example. This paper presents a method for relating spatial features to clinical outcome data. A set of parsimonious variables is extracted using sparse principal component analysis, producing simple yet characteristic features. The relation of these variables with clinical data is then established using a regression model. The result may be visualized as patterns of anatomical variation related to clinical outcome. In the present application, landmark-based shape data of the corpus callosum is analyzed in relation to age, gender, and clinical tests of walking speed and verbal fluency. To put the data-driven sparse principal component method into perspective, we consider two alternative techniques, one where features are derived using a model-based wavelet approach, and one where the original variables are regressed directly on the outcome.     

Quantitative high-resolution gas chromatographic determination of stereoisomeric composition of chiral volatile compounds in the picogram range by ec-detection

A gas chromatographic method using electron capture detection for determination of the stereochemical composition of chiralolatile compounds, e.g., pheromones, at the picogram level is described. Substances of interest are analyzed as pentafluorobenzoate derivatives on fused silica capillary columns coated with CP Sil-88. This method was developed primarily for the quantitative analyses of stereoisomerism of the pheromone precursor, diprionol, in female sawflies,Neodiprion sertifer. It was possible to separate the stereoisomers showing (2S, 3S, 7R) and (2S, 3S, 7S) configurations. Resolution of the (2S, 3S, 7S)- and (2S, 3R, 7R)-diastereomers was high enough to allow the quantification of these stereoisomers. A quantitative analysis of the diprionol production in individualN. sertifer females yielded 7.5–9.7 ng/female.     

Updated US and Canadian normalization factors for TRACI 2.1

When LCA practitioners perform LCAs, the interpretation of the results can be difficult without a reference point to benchmark the results. Hence, normalization factors are important for relating results to a common reference. The main purpose of this paper was to update the normalization factors for the US and US-Canadian regions. The normalization factors were used for highlighting the most contributing substances, thereby enabling practitioners to put more focus on important substances, when compiling the inventory, as well as providing them with normalization factors reflecting the actual situation. Normalization factors were calculated using characterization factors from the TRACI 2.1 LCIA model. The inventory was based on US databases on emissions of substances. The Canadian inventory was based on a previous inventory with 2005 as reference, in this inventory the most significant substances were updated to 2008 data. The results showed that impact categories were generally dominated by a small number of substances. The contribution analysis showed that the reporting of substance classes was highly significant for the environmental impacts, although in reality, these substances are nonspecific in composition, so the characterization factors which were selected to represent these categories may be significantly different from the actual identity of these aggregates. Furthermore the contribution highlighted the issue of carefully examining the effects of metals, even though the toxicity based categories have only interim characterization factors calculated with USEtox. A need for improved understanding of the wide range of uncertainties incorporated into studies with reported substance classes was indentified. This was especially important since aggregated substance classes are often used in LCA modeling when information on the particular substance is missing. Given the dominance of metals to the human and ecotoxicity categories, it is imperative to refine the CFs within USEtox. Some of the results within this paper indicate that soil emissions of metals are significantly higher than we expect in actuality.