Progressive contour coding in the wavelet domain

This paper presents a new wavelet-based image contour coding technique, suitable for representing either shapes or generic contour maps. Starting from a contour map (e.g. a segmentation map or the result of a contour extraction operator), this is first converted in a one-dimensional signal. Coordinate jumps among different contour extremities are converted, if under a suitable threshold, into signal discontinuities which can be compactly represented in the wavelet domain. Otherwise, the exceeding discontinuities are coded as side information. This side information is minimized by an optimized contour segment sequencing. The obtained 1D signal is decomposed and coded in the wavelet domain by using a 1D version of an improved implementation of the SPIHT algorithm. This technique can efficiently code every kind of 2D contour map, from one to many unconnected contour segments. It guarantees a fully embedded progressive coding, state-of-art coding performance, good approximation capabilities for both open and closed contours, and visually graceful degradation at low bit-rates

Workspace optimization for a planar cable-suspended direct-driven robot

The present work is inspired by an industrial task, i.e. spray painting a large area by means of a robotic system consisting in a Cable-Driven Parallel Robot (CDPR). In many cases, the area of the robot workspace is smaller than the area to be painted. For this reason, the base of the robot has to be shifted several times during the painting process. These robots are referred to as Repetitive Workspace Robots (RWR). In other words, in order to accomplish the whole task, they need to be moved after they have completed a sub-task locally. A cable suspended CDPR is an ideal candidate for such tasks; it can be thin, light, flexible and cost-efficient. The question is: which is the best shape of the local workspace in these conditions? In fact, not always a larger area of the local workspace guarantees an efficient painting process. This is because the efficiency relies mainly on the shape rather than on the local workspace area itself. In this work we employ an index [Seriani S, Gallina P, Gasparetto A, 2014] to evaluate the efficiency of the workspace of a 2-link CDPR. Finally, we show how the index value changes in relation to some geometrical parameters of the robot, thus laying the foundations for a general design methodology

Immunogenetics of an antigen identified in both sheep and cattle sera.

SUMMARYAlloimmunization in sheep revealed an antigen specificity B1 which is also to be found in cattle sera. The molecular weight of the protein carrying B1 was greater in sheep than in cattle, whilst in both cases its isoelectric point was at pH 6·2. The electrophoretic position of the antigen suggests that the molecule carrying B1 might be a β-globulin. Family studies indicated that in both species B1 was inherited in a simple Mendelian manner, as if it were a product of a dominant alleleB1at an autosomal locusB

Progressive contour coding in the wavelet domain

This paper presents a new wavelet-based image contour coding technique, suitable for representing either shapes or generic contour maps. Starting from a contour map (e.g. a segmentation map or the result of an edge detector process), a unique one-dimensional signal is generated from the set of contour points. Coordinate jumps between contour extremities when under a tolerance threshold represent signal discontinuities but they can still be compactly coded in the wavelet domain. Exceeding threshold discontinuities are coded as side information. This side information and the amount of remaining discontinuity are minimized by an optimized contour segment sequencing. The obtained 1D signal is decomposed and coded in the wavelet domain by using a 1D extension of the SPIHT algorithm. The described technique can efficiently code any kind of 2D contour map, from one to many unconnected contour segments. It guarantees a fully embedded progressive coding, state-of-art coding performance, good approximation capabilities for both open and closed contours, and graceful visual degradation at low bit-rates

Development of n-DoF Preloaded structures for impact mitigation in cobots

A core issue in collaborative robotics is that of impact mitigation, especially when collisions happen with operators. Passively compliant structures can be used as the frame of the cobot, although, usually, they are implemented by means of a single-degree-offreedom (DoF). However, n-DoF preloaded structures offer a number of advantages in terms of flexibility in designing their behavior. In this work, we propose a comprehensive framework for classifying n-DoF preloaded structures, including one-, two-, and threedimensional arrays. Furthermore, we investigate the implications of the peculiar behavior of these structures-which present sharp stiff-to-compliant transitions at designdetermined load thresholds-on impact mitigation. To this regard, an analytical n-DoF dynamic model was developed and numerically implemented. A prototype of a 10DoF structure was tested under static and impact loads, showing a very good agreement with the model. Future developments will see the application of n-DoF preloaded structures to impact-mitigation on cobots and in the field of mobile robots, as well as to the field of novel architected materials

upper limb rehabilitation robotics after stroke a perspective from the university of padua italy

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Application of a low-cost camera on a UAV to estimate maize nitrogen-related variables

The development of small unmanned aerial vehicles and advances in sensor technology have made consumer digital cameras suitable for the remote sensing of vegetation. In this context, monitoring the in-field variability of maize (Zea mays L.), characterized by high nitrogen fertilization rates, with a low-cost color-infrared airborne system could be the basis for a site-specific nitrogen (N) fertilization support system. An experimental field with different N treatments applied to silage maize was monitored during the years 2014 and 2015. Images of the field and reference destructive measurements of above ground biomass, its N concentration and N uptake were taken at V6 and V9 development stages. Classical normalized difference vegetation indices (NDVI) and the indices adjusted by crop ground cover were calculated and regressed against the measured variables. Finally, image colorgrams were used to explore the potential of band-related information in variable estimation. A colorgram is a linear signal that summarizes the color content of each digital image. It is composed of a sequence of the frequency distribution curves of the camera bands, of their related parameters and of results of the principal components analysis applied to each image. The best predictors were found to be the ground cover and the adjusted green-based NDVI: regression equation at V9 resulted in R2 of 0.7 and RRMSE < 25% in external validation. Colorgrams did not improve prediction performance due to the spectral limitations of the camera. Therefore, the feasibility of the method should be tested in future research. In spite of limitations of sensor setup, the modified camera was able to estimate maize biomass due to the very high spatial resolution. Since the above ground biomass is a robust proxy of N status, the modified camera could be a promising tool for a low-cost N fertilization support system

The KULTURisk Regional Risk Assessment methodology for water-related natural hazards – Part 1: Physical–environmental assessment

Abstract. In recent years, the frequency of catastrophes induced by natural hazards has increased, and flood events in particular have been recognized as one of the most threatening water-related disasters. Severe floods have occurred in Europe over the last decade, causing loss of life, displacement of people and heavy economic losses. Flood disasters are growing in frequency as a consequence of many factors, both climatic and non-climatic. Indeed, the current increase of water-related disasters can be mainly attributed to the increase of exposure (elements potentially at risk in flood-prone area) and vulnerability (i.e. economic, social, geographic, cultural and physical/environmental characteristics of the exposure). Besides these factors, the undeniable effect of climate change is projected to strongly modify the usual pattern of the hydrological cycle by intensifying the frequency and severity of flood events at the local, regional and global scale. Within this context, the need for developing effective and pro-active strategies, tools and actions which allow one to assess and (possibly) to reduce the flood risks that threatens different relevant receptors becomes urgent. Several methodologies to assess the risk posed by water-related natural hazards have been proposed so far, but very few of them can be adopted to implement the last European Flood Directive (FD). This paper is intended to introduce and present a state-of-the-art Regional Risk Assessment (RRA) methodology to appraise the risk posed by floods from a physical–environmental perspective. The methodology, developed within the recently completed FP7-KULTURisk Project (Knowledge-based approach to develop a cULTUre of Risk prevention – KR) is flexible and can be adapted to different case studies (i.e. plain rivers, mountain torrents, urban and coastal areas) and spatial scales (i.e. from catchment to the urban scale). The FD compliant KR-RRA methodology is based on the concept of risk being function of hazard, exposure and vulnerability. It integrates the outputs of various hydrodynamic models with site-specific bio-geophysical and socio-economic indicators (e.g. slope, land cover, population density, economic activities etc.) to develop tailored risk indexes and GIS-based maps for each of the selected receptors (i.e. people, buildings, infrastructure, agriculture, natural and semi-natural systems, cultural heritage) in the considered region. It further compares the baseline scenario with alternative scenarios, where different structural and/or non-structural mitigation measures are planned and eventually implemented. As demonstrated in the companion paper (Part 2, Ronco et al., 2014), risk maps, along with related statistics, allow one to identify and classify, on a relative scale, areas at risk which are more likely to be affected by floods and support the development of strategic adaptation and prevention measures to minimizing flood impacts. In addition, the outcomes of the RRA can be eventually used for a further socio-economic assessment, considering the tangible and intangible costs as well as the human dimension of vulnerability