Modeling sleep mode gains in energy-aware networks

Nowadays two main approaches are being pursued to reduce energy consumption of networks: the use of sleep modes in which devices enter a low-power state during inactivity periods, and the adoption of energy proportional mechanisms where the device architecture is designed to make energy consumption proportional to the actual load. Common to all the proposals is the evaluation of energy saving performance by means of simulation or experimental evidence, which typically consider a limited set of benchmarking scenarios.     

Hierarchical mesh segmentation based on fitting primitives

In this paper, we describe a hierarchical face clustering algorithm for triangle meshes based on fitting primitives belonging to an arbitrary set. The method proposed is completely automatic, and generates a binary tree of clusters, each of which is fitted by one of the primitives employed. Initially, each triangle represents a single cluster; at every iteration, all the pairs of adjacent clusters are considered, and the one that can be better approximated by one of the primitives forms a new single cluster. The approximation error is evaluated using the same metric for all the primitives, so that it makes sense to choose which is the most suitable primitive to approximate the set of triangles in a cluster. Based on this approach, we have implemented a prototype that uses planes, spheres and cylinders, and have experimented that for meshes made of 100 K faces, the whole binary tree of clusters can be built in about 8 s on a standard PC. The framework described here has natural application in reverse engineering processes, but it has also been tested for surface denoising, feature recovery and character skinning.     

Globally convergent autocalibration using interval analysis

We address the problem of autocalibration of a moving camera with unknown constant intrinsic parameters. Existing autocalibration techniques use numerical optimization algorithms whose convergence to the correct result cannot be guaranteed, in general. To address this problem, we have developed a method where an interval branch-and-bound method is employed for numerical minimization. Thanks to the properties of interval analysis this method converges to the global solution with mathematical certainty and arbitrary accuracy and the only input information it requires from the user are a set of point correspondences and a search interval. The cost function is based on the Huang-Faugeras constraint of the essential matrix. A recently proposed interval extension based on Bernstein polynomial forms has been investigated to speed up the search for the solution. Finally, experimental results are presented.     

Fabrication of photoactive heterostructures based on quantum dots decorated with Au nanoparticles

Silica based multifunctional heterostructures, exhibiting near infrared (NIR) absorption (650–1200 nm) and luminescence in the visible region, represent innovative nanosystems useful for diagnostic or theranostic applications. Herein, colloidal synthetic procedures are applied to design a photoactive multifunctional nanosystem. Luminescent silica (SiO₂) coated quantum dots (QDs) have been used as versatile nanoplatforms to assemble on their surface gold (Au) seeds, further grown into Au spackled structures. The synthesized nanostructures combine the QD emission in the visible region, and, concomitantly, the distinctive NIR absorption of Au nanodomains. The possibility of having multiple QDs in a single heterostructure, the SiO₂ shell thickness, and the extent of Au deposition onto SiO₂ surface have been carefully controlled. The work shows that a single QD entrapped in 16 nm thick SiO₂ shell, coated with Au speckles, represents the most suitable geometry to preserve the QD emission in the visible region and to generate NIR absorption from metal NPs. The resulting architectures present a biomedical potential as an effective optical multimodal probes and as promising therapeutic agents due to the Au NP mediated photothermal effect.     

Geographic knowledge extraction and semantic similarity in OpenStreetMap

In recent years, a web phenomenon known as Volunteered Geographic Information (VGI) has produced large crowdsourced geographic data sets. OpenStreetMap (OSM), the leading VGI project, aims at building an open-content world map through user contributions. OSM semantics consists of a set of properties (called ‘tags’) describing geographic classes, whose usage is defined by project contributors on a dedicated Wiki website. Because of its simple and open semantic structure, the OSM approach often results in noisy and ambiguous data, limiting its usability for analysis in information retrieval, recommender systems and data mining. Devising a mechanism for computing the semantic similarity of the OSM geographic classes can help alleviate this semantic gap. The contribution of this paper is twofold. It consists of (1) the development of the OSM Semantic Network by means of a web crawler tailored to the OSM Wiki website; this semantic network can be used to compute semantic similarity through co-citation measures, providing a novel semantic tool for OSM and GIS communities; (2) a study of the cognitive plausibility (i.e. the ability to replicate human judgement) of co-citation algorithms when applied to the computation of semantic similarity of geographic concepts. Empirical evidence supports the usage of co-citation algorithms—SimRank showing the highest plausibility—to compute concept similarity in a crowdsourced semantic network.     

A soft-input soft-output APP module for iterative decoding ofconcatenated codes

Concatenated coding schemes consist of the combination of two or more simple constituent encoders and interleavers. The parallel concatenation known as “turbo code” has been shown to yield remarkable coding gains close to theoretical limits, yet admitting a relatively simple iterative decoding technique. The recently proposed serial concatenation of interleaved codes may offer superior performance to that of turbo codes. In both coding schemes, the core of the iterative decoding structure is a soft-input soft-output (SISO) a posteriori probability (APP) module. In this letter, we describe the SISO APP module that updates the APP's corresponding to the input and the output bits, of a code, and show how to embed it into an iterative decoder for a new hybrid concatenation of three codes, to fully exploit the benefits of the proposed SISO APP module     

A model approach to assess the long-term trends of indirect photochemistry in lake water. The case of Lake Maggiore (NW Italy)

A model-based approach is here developed and applied to predict the long-term trends of indirect photochemical processes in the surface layer (5 m water depth) of Lake Maggiore, NW Italy. For this lake, time series of the main parameters of photochemical importance that cover almost two decades are available. As a way to assess the relevant photochemical reactions, the modelled steady-state concentrations of important photogenerated transients (^•OH, ³CDOM* and CO₃^-•) were taken into account. A multivariate analysis approach was adopted to have an overview of the system, to emphasise relationships among chemical, photochemical and seasonal variables, and to highlight annual and long-term trends. Over the considered time period, because of the decrease of the dissolved organic carbon (DOC) content of water and of the increase of alkalinity, a significant increase is predicted for the steady-state concentrations of the radicals ^•OH and CO₃^−•. Therefore, the photochemical degradation processes that involve the two radical species would be enhanced. Another issue of potential photochemical importance is related to the winter maxima of nitrate (a photochemical ^•OH source) and the summer maxima of DOC (^•OH sink and ³CDOM* source) in the lake water under consideration. From the combination of sunlight irradiance and chemical composition data, one predicts that the processes involving ^•OH and CO₃^−• would be most important in spring, while the reactions involving ³CDOM* would be most important in summer.