Information Gathering in Ad-Hoc Radio Networks with Tree Topology

We study the problem of information gathering in ad-hoc radio networks without collision detection, focussing on the case when the network forms a tree, with edges directed towards the root. Initially, each node has a piece of information that we refer to as a rumor. Our goal is to design protocols that deliver all rumors to the root of the tree as quickly as possible. The protocol must complete this task within its allotted time even though the actual tree topology is unknown when the computation starts. In the deterministic case, assuming that the nodes are labeled with small integers, we give an O(n)-time protocol that uses unbounded messages, and an O(n log n)-time protocol using bounded messages, where any message can include only one rumor. We also consider fire-and-forward protocols, in which a node can only transmit its own rumor or the rumor received in the previous step. We give a deterministic fire-and- forward protocol with running time O(n^1.5), and we show that it is asymptotically optimal. We then study randomized algorithms where the nodes are not labelled. In this model, we give an O(n log n)-time protocol and we prove that this bound is asymptotically optimal

Dense Motion Estimation for Smoke

Motion estimation for highly dynamic phenomena such as smoke is an open challenge for Computer Vision. Traditional dense motion estimation algorithms have difficulties with non-rigid and large motions, both of which are frequently observed in smoke motion. We propose an algorithm for dense motion estimation of smoke. Our algorithm is robust, fast, and has better performance over different types of smoke compared to other dense motion estimation algorithms, including state of the art and neural network approaches. The key to our contribution is to use skeletal flow, without explicit point matching, to provide a sparse flow. This sparse flow is upgraded to a dense flow. In this paper we describe our algorithm in greater detail, and provide experimental evidence to support our claims.Comment: ACCV201

Geodiversity assessment of Paraná state (Brazil): an innovative approach

Geodiversity is considered as the natural range of geological, geomorphological, and soil features, including their assemblages, relationships, properties, interpretations, and systems. A method developed for the quantitative assessment of geodiversity was applied to Parana ́ , a Brazilian state with an area of about 200,000 km2. The method is based on the overlay of a grid over different maps at scales ranging from 1/500,000 to 1/650,000, with the final Geodiversity Index the sum of five partial indexes calculated on a 25 9 25 km grid. The partial indexes represent the main components of geodi- versity, including geology (stratigraphy and lithology), geomorphology, paleontology, and soils. The fifth partial index covers mineral occurrences of geodiversity, such precious stones and metals, energy and industrial minerals, mineral waters, and springs. The Geodiversity Index takes the form of an isoline map that can be used as a tool in land-use planning, particularly in identifying priority areas for conservation, management, and use of natural resources at the state level.The Portuguese authors express their gratitude for the financial support given by the Fundacao para a Ciencia e a Tecnologia to the Centro de Geologia da Universidade do Porto, which partially supports this research. The Brazilian author expresses his gratitude for the financial support given by the CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico) (Process Number 200074/2011-3)

Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy)

Recent advances in spatial methods of digital elevation model (DEMs) analysis have addressed many research topics on the assessment of morphometric parameters of the landscape. Development of computer algorithms for calculating the geomorphometric properties of the Earth’s surface has allowed for expanding of some methods in the semi-automatic recognition and classification of landscape features. In such a way, several papers have been produced, documenting the applicability of the landform classification based on map algebra. The Topographic Position Index (TPI) is one of the most widely used parameters for semi-automated landform classification using GIS software. The aim was to apply the TPI classes for landform classification in the Basilicata Region (Southern Italy). The Basilicata Region is characterized by an extremely heterogeneous landscape and geological features. The automated landform extraction, starting from two different resolution DEMs at 20 and 5 m-grids, has been carried out by using three different GIS software: Arcview, Arcmap, and SAGA. Comparison of the landform maps resulting from each software at a different scale has been realized, furnishing at the end the best landform map and consequently a discussion over which is the best software implementation of the TPI method

Headwater Influences on Downstream Water Quality

We investigated the influence of riparian and whole watershed land use as a function of stream size on surface water chemistry and assessed regional variation in these relationships. Sixty-eight watersheds in four level III U.S. EPA ecoregions in eastern Kansas were selected as study sites. Riparian land cover and watershed land use were quantified for the entire watershed, and by Strahler order. Multiple regression analyses using riparian land cover classifications as independent variables explained among-site variation in water chemistry parameters, particularly total nitrogen (41%), nitrate (61%), and total phosphorus (63%) concentrations. Whole watershed land use explained slightly less variance, but riparian and whole watershed land use were so tightly correlated that it was difficult to separate their effects. Water chemistry parameters sampled in downstream reaches were most closely correlated with riparian land cover adjacent to the smallest (first-order) streams of watersheds or land use in the entire watershed, with riparian zones immediately upstream of sampling sites offering less explanatory power as stream size increased. Interestingly, headwater effects were evident even at times when these small streams were unlikely to be flowing. Relationships were similar among ecoregions, indicating that land use characteristics were most responsible for water quality variation among watersheds. These findings suggest that nonpoint pollution control strategies should consider the influence of small upland streams and protection of downstream riparian zones alone is not sufficient to protect water quality

Use of remote sensing to identify spatial risk factors for malaria in a region of declining transmission: a cross-sectional and longitudinal community survey

<p>Abstract</p> <p>Background</p> <p>The burden of malaria has decreased dramatically within the past several years in parts of sub-Saharan Africa. Further malaria control will require targeted control strategies based on evidence of risk. The objective of this study was to identify environmental risk factors for malaria transmission using remote sensing technologies to guide malaria control interventions in a region of declining burden of malaria.</p> <p>Methods</p> <p>Satellite images were used to construct a sampling frame for the random selection of households enrolled in prospective longitudinal and cross-sectional surveys of malaria parasitaemia in Southern Province, Zambia. A digital elevation model (DEM) was derived from the Shuttle Radar Topography Mission version 3 DEM and used for landscape characterization, including landforms, elevation, aspect, slope, topographic wetness, topographic position index and hydrological models of stream networks.</p> <p>Results</p> <p>A total of 768 individuals from 128 randomly selected households were enrolled over 21 months, from the end of the rainy season in April 2007 through December 2008. Of the 768 individuals tested, 117 (15.2%) were positive by malaria rapid diagnostic test (RDT). Individuals residing within 3.75 km of a third order stream were at increased risk of malaria. Households at elevations above the baseline elevation for the region were at decreasing risk of having RDT-positive residents. Households where new infections occurred were overlaid on a risk map of RDT positive households and incident infections were more likely to be located in high-risk areas derived from prevalence data. Based on the spatial risk map, targeting households in the top 80^thpercentile of malaria risk would require malaria control interventions directed to only 24% of the households.</p> <p>Conclusions</p> <p>Remote sensing technologies can be used to target malaria control interventions in a region of declining malaria transmission in southern Zambia, enabling a more efficient use of resources for malaria elimination.</p