On the structural nature of cooperation in distributed network localization

We demonstrate analytically that the contribution of cooperation in improving the accuracy of distributed network localization has a fundamentally structural nature, rather then statistical as widely believed. To this end we first introduce a new approach to build Fisher Information Matrices (FIMs), in which the individual contribution of each cooperative pair of nodes is captured explicitly by a corresponding information vector. The approach offers new insight onto the structure of FIMs, enabling us to easily account for both anchor and node location uncertainties in assessing lower bounds on localization errors. Using this construction it is surprisingly found that in the presence of node location uncertainty and regardless of ranging error variances or network size, the Fisher information matrix (FIM) terms corresponding to the information added by node-to-node cooperation nearly vanish. In other words, the analysis reveals that the key contribution of cooperation in network localization is not to add statistical node-to-node information (in the Fisher sense), but rather to provide a structure over which information is better exploited

An ensemble of classifiers based on different texture descriptors for texture classification

Abstract Here we propose a system that incorporates two different state-of-the-art classifiers (support vector machine and gaussian process classifier) and two different descriptors (multi local quinary patterns and multi local phase quantization with ternary coding) for texture classification. Both the tested descriptors are an ensemble of stand-alone descriptors obtained using different parameters setting (the same set is used in each dataset). For each stand-alone descriptor we train a different classifier, the set of scores of each classifier is normalized to mean equal to zero and standard deviation equal to one, then all the score sets are combined by the sum rule. Our experimental section shows that we succeed in building a high performance ensemble that works well on different datasets without any ad hoc parameters tuning. The fusion among the different systems permits to outperform SVM where the parameters and kernels are tuned separately in each dataset, while in the proposed ensemble the linear SVM, with the same parameter cost in all the datasets, is used

Hierarchical 1D/3D Approach for the Development of a Turbulent Combustion Model Applied to a VVA Turbocharged Engine. Part I: Turbulence Model☆

Abstract It is widely recognized that air-fuel mixing, combustion and pollutant formation inside internal combustion engines are strongly influenced by the spatial and temporal evolution of both marco- and micro- turbulent scales. Particularly, in spark ignited engines, the generation of a proper level of turbulence intensity for the correct development of the flame front is traditionally based on the onset, during the intake and compression strokes, of a tumbling macro-structure. Recently, in order to both reduce pumping losses due to throttling and develop advanced and flexible engine control strategies, fully variable valve actuation systems have been introduced, capable of simultaneously governing both valve phasing and lift. Despite the relevant advantages in terms of intake system efficiency, this technology introduces uncertainties on the capability of the intake port/valve assembly to generate, at low loads, sufficiently coherent and stable structures, able therefore to promote adequate turbulence levels towards the end of the compression, with relevant effects on the flame front development. It is a common knowledge that 3D-CFD codes are able to describe the evolution of the in-cylinder flow field and of the subsequent combustion process with good accuracy; however, they require too high computational time to analyze the engine performance for the whole operating domain. On the contrary, this task is easily accomplished by 1D codes, where, however, the combustion process is usually derived from experimental measurements of the in-cylinder pressure trace (Wiebe correlation). This approach is poorly predictive for the simulation of operating conditions relevantly different from the experimental ones. To overcome the above described issues, enhanced physical models for the description of in-cylinder turbulence evolution and combustion to be included in a 1D modeling environment are mandatory. In the present paper (part I), a 0D (i.e. homogeneous and isotropic) phenomenological (i.e. sensitive to the variation of operative parameters such as valve phasing, valve lift, intake and exhaust pressure levels, etc.) turbulence model belonging to the K-k model family is presented in detail. The model is validated against in-cylinder results provided by 3D-CFD analyses carried ou

Hierarchical 1D/3D Approach for the Development of a Turbulent Combustion Model Applied to a VVA Turbocharged Engine. Part II: Combustion Model

As discussed in the part I of this paper, 3D models represent a useful tool for a detailed description of the mean and turbulent flow fields inside the engine cylinder. 3D results are utilized to develop and validate a 0D phenomenological turbulence model, sensitive to the variation of operative parameters such as valve phasing, valve lift, engine speed, etc. In part II of this paper, a 0D phenomenological combustion model is presented, as well. It is based on a fractal description of the flame front and is able to sense each of the fuel properties, the operating conditions (air-to-fuel ratio, spark advance, boost level) and the combustion chamber geometry. In addition, it is capable to properly handle different turbulence levels predicted by means of the turbulence model presented in the part I. The turbulence and combustion models are included, through user routines, in the commercial software GT-Power". With reference to a small twin-cylinder VVA turbocharged engine, the turbulence/combustion model, once properly tuned, is finally used to calculate in-cylinder pressure traces, rate of heat release and overall engine performance at full load operations and brake specific fuel consumption at part load, as well. An excellent agreement between numerical forecasts and experimental evidence is obtained

Computational Analysis of Extracellular Calcium Effects on an Improved Human Ventricular Action Potential Model

A decrease in extracellular calcium concentration ([Ca 2+ ] o ) prolongs the action potential (AP) Introduction The effects of extracellular concentration of ionized calcium ([Ca 2+ ] o ) on cardiac electrophysiology have been already discussed in previous works QT c prolongation is associated with an increased risk of early after-depolarization and triggered arrhythmias, and the same applies to abnormal QT c shortening: Methods The ORd model of human ventricular myocyte [9] provided the basis for simulations in this study. Since ICaL is the current mainly affected by [Ca 2+ ] o changes, its formulation has been revisited, especially its modulation of calcium-dependent (CDI) and voltage-dependent (VDI) inactivation. Ca 2+ modulation: n gate One of the features of ORd model, based on experiments by Kim et al. [11], is that CDI has been considered to function as a faster VDI, activated by high calcium concentration in the subspace region ([Ca] ss ]. Thus, both VDI and CDI mechanisms are voltagedependent and a new state variable has been introduced to modulate them: n gate. It represents the fraction of channel operating in CDI mode, and it is the only state variable, among the ones involved in ICaL kinetics, to be directly dependent on [Ca] ss . The n formulation, based on interaction between Ca 2+ and Calmodulin bound to L-type Ca 2+ -channels cinc.org Computing in Cardiology 2012; 39:873-876

Comment on the paper: 'novel approach to estimate kidney and cyst volumes using mid-slice magnetic resonance images in polycystic kidney disease'

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An Automatic Framework for the Non-rigid Alignment of Electroanatomical Maps and Preoperative Anatomical Scans in Atrial Fibrillation

In atrial fibrillation, electro-anatomical maps (EAM) are used for ablation guidance. Yet, the anatomy reconstructed by the navigation system is known to be poorly accurate. This makes catheter navigation challenging and, as such, might affects ablation’s outcome. To ease navigation, existing systems allow co-registering EAMs with pre-operative MR scans by rigidly matching a set of manual landmarks. Nevertheless, the deformation between the two datasets is highly non-rigid. The aim of this work was therefore to develop a framework for the non-rigid alignment of EAMs and anatomical scans to improve ablation guidance