Aerosol Extinction Uncertainty Determination for a Laser-Based Detecting System

Quantitative measurement of optic and aerosolic property of troposphere may be carried out from lidar system more easily and with low marginal cost than other system (i.e. satellite observation). The aim of this work is to show how extinction coefficient and water vapor concentration in troposphere may be educed from lidar signals at several altitudes and how uncertainty is close to acceptable value. Real data observations will be presented to demostrate uncertainty range on aerosolic extinction coefficient function

Editorial: Special Issue on Environmental Measurement and Instrumentation

This Special Issue contains expanded and enhanced versions of selected papers presented at the 2013 IMEKO TC19 Symposium on Environmental Monitoring

Sparsity of the Field Signal-Based Method for Improving Spatial Resolution in Antenna Sensor Array Processing

The goal of array processing is to gather information from propagating radio-wave signals, as their Direction Of Arrival (DOA). The estimation of the DOA can be carried out by extracting the information of interest from the steering vector relevant to the adopted antenna sensor array. Such task can be accomplished in a number of different ways. However, in source estimation problems, it is essential to make use of a processing algorithm which feature not only good accuracy under ideal working conditions, but also robustness against non-idealities such as noise, limitations in the amount of collectible data, correlation between the sources, and modeling errors. In this work particular attention is devoted to spectrum estimation approaches based on sparsity. Conventional algorithms based on Beamforming fail wherein the radio sources are not within Rayleigh resolution range which is a function of the number of sensors and the dimension of the array. DOA estimation techniques such as MUSIC (MUltiple Signal Classifications) allow having a larger spatial resolution compared to Beamforming-based procedures, but if the sources are very close and the Signal to Noise Ratio (SNR) level is low, the resolution turns to be low as well. A better resolution can be obtained by exploiting sparsity: if the number of sources is small, the power spectrum of the signal with respect to the location is sparse. In this way, sparsity can enhance the accuracy of the estimation. In this paper, an estimation procedure based on the sparsity of the radio signals and useful to improve the conventional MUSIC method is presented and analyzed. The sparsity level is set in order to focus the signal energy only along the actual direction of arrival. The obtained numerical results have shown an improvement of the spatial resolution as well as a reduced error in DOA estimation with respect to conventional techniques

Locally conformal FDTD modeling of MEMS-Based antenna sensors for melanoma detection

The full-wave characterization of reconfigurable antenna sensors for non-invasive detection of melanoma is presented. To this end, an enhanced locally conformal finite-difference time-domain numerical procedure, based on a suitable normalization of the electromagnetic field-related quantities, is adopted. In this way, a physical insight in wave diffraction phenomena occurring in the radar monitoring of skin cancers, as well as in the natural resonant processes responsible for the performance of the considered class of devices is achieved. This, in turn, is important in order to enhance the device reliability, so optimizing the design cycle. In this respect, a suitable microelectro-mechanical-system-based sensor layout is proposed

An embedded beamformer for a PID-based trajectory sensing for an autonomous vehicle

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Design and Characterization of a Nanocomposite Pressure Sensor Implemented in a Tactile Robotic System

In this paper, we present the implementation of a new class of optical pressure sensors in a robotic tactile-sensing system based on polydimethylsiloxane (PDMS). The sensor consists of a tapered optical fiber, where an optical signal goes across, embedded into a PDMS–gold nanocomposite material (GNM). By applying different pressure forces onto the PDMS-based nanocomposite, changes in the optical transmittivity of the fiber can be detected in real time due to the coupling between the GNM and the tapered fiber region. The intensity reduction of a transmitted light is correlated to the pressure force magnitude. Light intensity is converted into an electric signal by a system suitable for robotic implementation. High sensitivity using forces by applying weights of a few grams is proved. Sensitivity on the order of 5 g is checked. A detailed algorithm for the detection of roughness and shapes by means of a robotic finger is proposed

Collaborative systems for telemedicine diagnosis accuracy

The transmission of medical data and the possibility for distant healthcare structures to share experiments about a given medical case raises several conceptual and technical questions. Good remote healthcare monitoring deals with more problems in personalized heath data processing compared to the traditional methods nowadays used in several parts of hospitals in the world. The adoption of telemedicine in the healthcare sector has significantly changed medical collaboration. However, to provide good telemedicine services through new technologies such as cloud computing, cloud storage, and so on, a suitable and adaptable framework should be designed. Moreover, in the chain of medical information exchange, between requesting agencies, including physicians, a secure and collaborative platform enhanced the decision-making process. This paper provides an in-depth literature review on the interaction that telemedicine has with cloud-based computing. On the other hand, the paper proposes a framework that can allow various research organizations, healthcare sectors, and government agencies to log data, develop collaborative analysis, and support decision-making. The electrocardiogram (ECG) and electroencephalogram EEG case studies demonstrate the benefit of the proposed approach in data reduction and high-fidelity signal processing to a local level; this can make possible the extracted characteristic features to be communicated to the cloud database

New generation of optical robotic sensor applied to small notch detection

In this paper the experimental application of a new class of an optical pressure sensor based on polydimethylsiloxane (PDMS)-Au is shown. The sensor consists of a tapered bended optical fiber, where an optical signal goes across, embedded into a PDMS-gold nanocomposite material (GNM) and it is used for scanning surfaces while it is moved automatically by a controlled servomotor. The sensor data during the scanning may be used for detecting a small notch on a beam. The experimental results are very encouraging for foreseeing successful use of this new sensor in robotic applications

Decimated Signal Diagonalization Method for Improved Spectral Leak Detection in Pipelines

none2siLeak detection is an important issue in piping that deals with the management of water resources; nowadays large amounts of water in the network are dispersed as reported in current scientific literature. Among the methods for leak detection in water pipes, spectral analysis is very interesting. A classical spectral method is fast Fourier transform, but in this paper, we present an alternative method of spectral analysis, which has higher performance in terms of resolution and fast processing, namely decimated signal diagonalization (DSD). It is a nonlinear, parametric method for fitting time domain signals represented in terms of exponentially damped time signals. The aim is to reconstruct the unknown components as the harmonic variables, estimating the fundamental complex frequencies, and amplitudes. The DSD method partly uses the principles of the filter diagonalization method (FDM), which constructs matrices of a generalized eigenvalue problem directly from measured time signals of arbitrary length. However, the DSD because of its windowing technique produces a considerable reduction of size of the original data matrix, and consequently acquisition time can be shorter. We have tested the DSD method for leak detection problem in an experimental zigzag pipeline. We show as the DSD method produces good results in terms of resolution than FDM one.restrictedLay-Ekuakille, Aime; Vergallo, PatriziaLAY EKUAKILLE, Aime; Vergallo, Patrizi