Augmented Thevenin Model for the Harmonic Analysis of Switching Circuits

This article addresses the use of the Thevenin equivalent model in the case of switching circuits. An augmented Thevenin model is proposed, based on a well-established augmented equivalent approach for the analysis of periodically switched linear networks. It can profitably be used to provide a time-invariant equivalent description of a switching network and to investigate on the harmonics behavior at any of its ports even upon the varying of one of its internal parameters. This makes the article interesting for harmonic analysis purposes as, for instance, in the analysis and troubleshooting of electromagnetic interference or in the monitoring of a system behavior through the assessment and analysis of some of its spectral components. The model has also the advantage to be simple in its implementation. The feasibility and potentiality of the method are verified via simulations and comparisons with the results obtained by applying the augmented equivalent approach to the case of a dc\u2013dc Buck converter

VoIP over WLAN: What about the Presence of Radio Interference?

In this chapter, the performance of VoIP over WLAN is analyzed under the effect of physical layer interference, in the presence and absence of cross-traffic. The goal is twofold: first to underline the importance of radio interference in the behavior of a WLAN when supporting VoIP applications; second to outline solutions to avoid interference and thus optimizing a VoIP call over aWLAN. To this aim, an experimental approach based on cross-layermeasurements is adopted, describing and commenting meaningful results obtained from a number of experiments conducted by the authors on a testbed operating in a semi-anechoic chamber and emulating two typical real life scenarios

Cross-Layer measurement on an IEEE 802.11g wireless network supporting MPEG-2 video streaming applications in the presence of interference

The performance of wireless local area networks supporting video streaming applications, based on MPEG-2 video codec, in the presence of interference is here dealt with. IEEE 802.11g standard wireless networks, that do not support QoS in according with IEEE 802.11e standard, are, in particular, accounted for and Bluetooth signals, additive white Gaussian noise, and competitive data traffic are considered as sources of interference. The goal is twofold: from one side, experimentally assessing and correlating the values that some performance metrics assume at the same time at different layers of an IEEE 802.11g WLAN delivering video streaming in the presence of in-channel interference; from the other side, deducing helpful and practical hints for designers and technicians, in order to efficiently assess and enhance the performance of an IEEE 802.11g WLAN supporting video streaming in some suitable setup conditions and in the presence of interference. To this purpose, an experimental analysis is planned following a cross-layer measurement approach, and a proper testbed within a semianechoic chamber is used. Valuable results are obtained in terms of signal-to-interference ratio, packet loss ratio, jitter, video quality, and interference data rate; helpful hints for designers and technicians are finally gained

MultiLink Analysis: Brain Network Comparison via Sparse Connectivity Analysis

Abstract The analysis of the brain from a connectivity perspective is revealing novel insights into brain structure and function. Discovery is, however, hindered by the lack of prior knowledge used to make hypotheses. Additionally, exploratory data analysis is made complex by the high dimensionality of data. Indeed, to assess the effect of pathological states on brain networks, neuroscientists are often required to evaluate experimental effects in case-control studies, with hundreds of thousands of connections. In this paper, we propose an approach to identify the multivariate relationships in brain connections that characterize two distinct groups, hence permitting the investigators to immediately discover the subnetworks that contain information about the differences between experimental groups. In particular, we are interested in data discovery related to connectomics, where the connections that characterize differences between two groups of subjects are found. Nevertheless, those connections do not necessarily maximize the accuracy in classification since this does not guarantee reliable interpretation of specific differences between groups. In practice, our method exploits recent machine learning techniques employing sparsity to deal with weighted networks describing the whole-brain macro connectivity. We evaluated our technique on functional and structural connectomes from human and murine brain data. In our experiments, we automatically identified disease-relevant connections in datasets with supervised and unsupervised anatomy-driven parcellation approaches and by using high-dimensional datasets

Predictors of rapid cognitive decline in Alzheimer\u27s disease: Results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing

Background: The AIBL study, which commenced in November 2006, is a two-center prospective study of a cohort of 1112 volunteers aged 60+. The cohort includes 211 patients meeting NINCDS-ADRDA criteria for Alzheimer\u27s disease (AD) (180 probable and 31 possible). We aimed to identify factors associated with rapid cognitive decline over 18 months in this cohort of AD patients. Methods: We defined rapid cognitive decline as a drop of 6 points or more on the Mini-Mental State Examination (MMSE) between baseline and 18-month follow-up. Analyses were also conducted with a threshold of 4, 5, 7 and 8 points, as well as with and without subjects who had died or were too severely affected to be interviewed at 18 months and after, both including and excluding subjects whose AD diagnosis was \u27possible\u27 AD. We sought correlations between rapid cognitive decline and demographic, clinical and biological variables. Results: Of the 211 AD patients recruited at baseline, we had available data for 156 (73.9%) patients at 18 months. Fifty-one patients were considered rapid cognitive decliners (32.7%). A higher Clinical Dementia Rating scale (CDR) and higher CDR \u27sum of boxes\u27 score at baseline were the major predictors of rapid cognitive decline in this population. Furthermore, using logistic regression model analysis, patients treated with a cholinesterase inhibitor (CheI) had a higher risk of being rapid cognitive decliners, as did males and those of younger age. Conclusions: Almost one third of patients satisfying established research criteria for AD experienced rapid cognitive decline. Worse baseline functional and cognitive status and treatment with a CheI were the major factors associated with rapid cognitive decline over 18 months in this population

Multi-Sensor UAV Application for Thermal Analysis on a Dry-Stone Terraced Vineyard in Rural Tuscany Landscape

Italian dry-stone wall terracing represents one of the most iconic features of agricultural landscapes across Europe, with sites listed among UNESCO World Heritage Sites and FAO Globally Important Agricultural Heritage Systems (GIAHS). The analysis of microclimate modifications induced by alterations of hillslope and by dry-stone walls is of particular interest for the valuation of benefits and drawbacks of terraces cultivation, a global land management technique. The aim of this paper is to perform a thermal characterization of a dry-stone wall terraced vineyard in the Chianti area (Tuscany, Italy), to detect possible microclimate dynamics induced by dry-stone terracing. The aerial surveys were carried out by using two sensors, in the Visible (VIS) and Thermal InfraRed (TIR) spectral range, mounted on Unmanned Aerial Vehicles (UAVs), with two different flights. Our results reveal that, in the morning, vineyard rows close to dry-stone walls have statistically lower temperatures with respect to the external ones. In the afternoon, due to solar insulation, temperatures raised to the same value for each row. The results of this early study, jointly with the latest developments in UAV and sensor technologies, justify and encourage further analyses on local climatic modifications in terraced landscapes