Rawseeds ground truth collection systems for indoor self-localization and mapping

A trustable and accurate ground truth is a key requirement for benchmarking self-localization and mapping algorithms; on the other hand, collection of ground truth is a complex and daunting task, and its validation is a challenging issue. In this paper we propose two techniques for indoor ground truth collection, developed in the framework of the European project Rawseeds, which are mutually independent and also independent on the sensors onboard the robot. These techniques are based, respectively, on a network of fixed cameras, and on a network of fixed laser scanners. We show how these systems are implemented and deployed, and, most importantly, we evaluate their performance; moreover, we investigate the possible fusion of their outputs.     

A super-peer model for resource discovery services in large-scale Grids

As deployed Grids increase from tens to thousands of nodes, peer-to-peer (P2P) techniques and protocols can be used to implement scalable services and applications. The super-peer model is a novel approach that helps the convergence of P2P models and Grid environments and can be used to deploy a P2P information service in Grids. A super-peer serves a single physical organization in a Grid, and manages metadata associated to the resources provided by the nodes of that organization. Super-peers connect to each other to form a peer network at a higher level. This paper examines how the super-peer model can handle membership management and resource discovery services in a multi-organizational Grid. A simulation analysis evaluates the performance of a resource discovery protocol; simulation results can be used to tune protocol parameters in order to increase search efficiency.     

A graph-based approach for extracting terminological properties from information sources with heterogeneous formats

The problem of handling both the integration and the cooperation of a large number of information sources characterised by heterogeneous representation formats is a challenging issue. In this context, a central role can be played by the knowledge about the semantic relationships holding between concepts belonging to different information sources (intersource properties). In this paper, we propose a semiautomatic approach for extracting two kinds of intersource properties, namely synonymies and homonymies, from heterogeneous information sources. In order to carry out the extraction task, we introduce both a conceptual model, for representing involved sources, and a metrics, for measuring the strength of the semantic relationships holding among concepts represented within the same source.     

Compared Analysis of Metro Networks Supported by Graph Theory

This paper brings into focus the topological and geographical evaluation of metro networks through the definition of a methodological approach based on a set of indicators, a lot of which are defined in the sector literature. Once the methodology was stated, the results of an application on the metro networks of 13 big metropolitan areas were illustrated. Statistical comparative analyses are proposed to classify networks.     

A Technique for Extracting Sub-source Similarities from Information Sources Having Different Formats

In this paper we propose a semi-automatic technique for deriving the similarity degree between two portions of heterogeneous information sources (hereafter, sub-sources). The proposed technique consists in two phases: the first one selects the most promising pairs of sub-sources, whereas the second one computes the similarity degree relative to each promising pair. We show that the detection of sub-source similarities is a special case (and a very interesting one, for semi-structured information sources) of the more general problem of Scheme Match. In addition, we present a real example case to clarify the proposed technique, a set of experiments we have conducted to verify the quality of its results, a discussion about its computational complexity and its classification in the context of related literature. Finally, we discuss some possible applications which can benefit by derived similarities.     

Squaring down LTI systems: A geometric approach

In this paper, the problem of reducing a given LTI system into a left or right invertible one is addressed and solved with the standard tools of the geometric control theory. First, it will be shown how an LTI system can be turned into a left invertible system, thus preserving key system properties like stabilizability, phase minimality, right invertibility, relative degree and infinite zero structure. Moreover, the additional invariant zeros introduced in the left invertible system thus obtained can be arbitrarily assigned in the complex plane. By duality, the scheme of a right inverter will be derived straightforwardly. Moreover, the squaring down problem will be addressed. In fact, when the left and right reduction procedures are applied together, a system with an unequal number of inputs and outputs is turned into a square and invertible system. Furthermore, as an example it will be shown how these techniques may be employed to weaken the standard assumption of left invertibility of the plant in many optimization problems.     

Robust non-fragile LQ controllers: The static state feedback case

This paper describes the synthesis of non-fragile or resilient regulators for linear systems. A general framework for fragility is described using state-space methodologies, and the LQ/H₂ static state-feedback problem is examined in detail. We discuss the multiplicative structured uncertainties case, and propose remedies of the fragility problem using an optimization programming framework via matrix inequalities. A special case that leads to a convex optimization framework via linear matrix inequalities (LMIs) will be considered. The benchmark problem is taken as an example to show how special controller gain variations can affect the performance of the closed-loop system.     

Reliability as Tool for Hydraulic Network Planning

This paper presents a methodology to evaluate the reliability of water distribution systems that can be used in the design phase and for identifying repair works to be carried out on existing systems. The methodology is based on the statistical analysis of dimensionless performance indices (hydraulic performance indices) derived from a large number of simulations of various water system demand scenarios and∕or operating conditions. The hydraulic reliability index is assumed as the probability that, under a given operating condition, the hydraulic performance index will be above a certain threshold. Finally, the system's overall reliability (mechanical + hydraulic) is estimated using the overall reliability index, which is defined by the weighted mean of the hydraulic performance indices obtained for the various operating conditions. A case study using this methodology shows the concrete possibilities of applying this approach to a wide spectrum of cases, and the small influence on overall system reliability normally exerted by such events as the failure of links, pipes, and valves.     

Accurate neural model identification of measurement devices

A neural approach to modeling measurement devices is presented. This approach allows the usual components of a measurement apparatus (transducers, filters, amplifiers, analog-to-digital converters, etc.) to be easily modeled by means of suitably trained artificial neural networks. Two applications regarding analog and mixed analog/digital devices are reported, highlighting the peculiarity of this approach and the accuracy that can be obtained.