A Fuzzy Approach to Reduce Delays at Signalized Road Intersections

In this paper a fuzzy approach is proposed to reduce delay at isolated intersections by using as indicator the intersection saturation degree. The proposed system co mbines fixed-duration cycle and fuzzy calculus to reduce the overall delay without giving too much penalty to some traffic streams. To obtain the intended goal, the green times are modified according to the measured traffic flow values and by using a fuzzy procedure. Measured traffic flo ws are considered as fuzzy quantities because of their uncertainty and/or imprecision. A test examp le is analysed to show the benefits of the fuzzy controlled intersection with respect to a crispy controlled one. The results show that the use of the fu zzy procedure reduces the total and average delay at the intersection by modifying the phase duration according to sampled traffic flows

Retrieving the Effective Parameters of an Electromagnetic Metamaterial Using the Nicolson-Ross-Weir Method: An Analytic Continuation Problem Along the Path Determined by Scattering Parameters

Electromagnetic metamaterials (MMs) are composite structures that allow one to potentially develop unique and innovative microwave, millimetre wave, and optical devices due to their unusual physical properties. In this process, their electromagnetic characterization plays a fundamental role. Various procedures have been proposed to accomplish this task, but the Nicolson-Ross-Weir (NRW) method still appears to be the most commonly adopted one even though it is afflicted by the severe issue of branch ambiguity. In this paper, we have demonstrated that rigorously, as the branch ambiguity can be entirely overcome through the analytic continuation of a specific analytic logarithm element along the path determined in the complex plane by the scattering parameters of an MM under analysis. Furthermore, the underlying relationship between analytic continuation, phase unwrapping approach, implemented through a procedure devised by Oppenheim and Schafer for the homomorphic treatment of signals (hereafter named PUNWOS), and the Kronig-Kramers relation has been discussed and enlightened, demonstrating the full equivalence among the methods. To clarify this aspect, a couple of numerical examples is presented. The results discussed in this study open the possibility of employing the vast theoretical equipment developed in the phase unwrapping field to achieve the retrieval of MMs' effective parameters when the NRW method is applicable

A Geometric Fuzzy-Based Approach for Airport Clustering

Airport classification is a common need in the air transport field due to several purposes—such as resource allocation, identification of crucial nodes, and real-time identification of substitute nodes—which also depend on the involved actors’ expectations. In this paper a fuzzy-based procedure has been proposed to cluster airports by using a fuzzy geometric point of view according to the concept of unit-hypercube. By representing each airport as a point in the given reference metric space, the geometric distance among airports—which corresponds to a measure of similarity—has in fact an intrinsic fuzzy nature due to the airport specific characteristics. The proposed procedure has been applied to a test case concerning the Italian airport network and the obtained results are in line with expectations

Electrostatic Micro-Electro-Mechanical-Systems (MEMS) Devices: A Comparison Among Numerical Techniques for Recovering the Membrane Profile

In this work, numerical techniques based on Shooting procedure, Relaxation scheme and Collocation technique have been used for recovering the profile of the membrane of a 1D electrostatic Micro-Electro-Mechanical-Systems (MEMS) device whose analytic model considers |E| proportional to the membrane curvature. The comparison among these numerical techniques has put in evidence the pros and cons of each numerical procedure. Furthermore, useful convergence conditions which ensure the absence of ghost solutions, and a new condition of existence and uniqueness for the solution of the considered differential MEMS model, are obtained and discussed

INDEPENDENT COMPONENT ANALYSIS AND DISCRETE WAVELET TRANSFORM FOR ARTIFACT REMOVAL IN BIOMEDICAL SIGNAL PROCESSING

Recent works have shown that artifact removal in bi omedical signals can be performed by using Discrete Wavelet Transform (DWT) or Independent Component Analysis (ICA). It results often very difficult to remove some artifacts because they could be superimposed on the recordings and they could corrupt the signals in the frequency domain. The two conditions could compromise the performance of both DWT and ICA methods. In this study we show that if the two methods are jointly implemented, it is possible to improve the performances for the artifact rejection procedure. We discuss in detail the new method and we also show how this method provides advantages with respect to DWT of ICA procedure. Finally, we tested the new approach on real data

Adaptive Image Contrast Enhancement by Computing Distances into a 4-Dimensional Fuzzy Unit Hypercube

A new fuzzy procedure for adaptive gray-level image contrast enhancement (CE) is presented in this paper. Starting from the pixels belonging to a normalized gray-level image, an appropriate smooth S-shaped fuzzy membership function (MF) is considered for gray-scale transformation and is adaptively developed through noise reduction and information loss minimization. Then, a set of fuzzy patches is extracted from the MF, and for each support of each patch, we compute four ascending-order statistics that become points inside a 4-D fuzzy unit hypercube after a suitable fuzzification step. CE is performed by computing the distances among the above points and the points of maximum darkness and maximum brightness (special vertexes in the hypercube), and by determining the rotation of the tangent line to the MF around a crucial point where fuzzy patches and the MF coexist. The proposed procedure enables high CE in all the treated images with performance that is fully comparable with that obtained by three more sophisticated fuzzy techniques and by standard histogram equalization

Path Loss Prediction Using Fuzzy Inference System and Ellipsoidal Rules

It is well known as the prediction of radio wave path loss in urban environment plays a key role in order to correctly plan wireless systems and mobile communication networks. To obtain more flexible prediction models able to give accurate results, in recent years Soft computing Techniques has been exploited. In this study, a novel approach based on ellipsoidal fuzzy inference system EFIS is investigated. Results compared with those provided by the Okumura Hata model and the standard Fuzzy Inference System approach (FIS) show superior performances of the EFIS approach

Joint use of eddy current imaging and fuzzy similarities to assess the integrity of steel plates

AbstractSteel plates bi-axially loaded are characterized by mechanical deformations whose 2D image representations are very difficult to achieve. In this work, the authors propose an innovative approach based on eddy current techniques for obtaining 2D electrical maps to assess the mechanical integrity of a steel plate. The procedure, also exploiting fuzzy similarity computations, translates the problem of the assessment of the mechanical integrity of a steel plate into a suitable classification problem. The results obtained by this proposed procedure show performances comparable to those provided by well-established soft computing approaches with a higher computational complexity

Relationship between coronary plaque morphology of the left anterior descending artery and 12 months clinical outcome: the CLIMA study

Abstract Aims The CLIMA study, on the relationship between coronary plaque morphology of the left anterior descending artery and twelve months clinical outcome, was designed to explore the predictive value of multiple high-risk plaque features in the same coronary lesion [minimum lumen area (MLA), fibrous cap thickness (FCT), lipid arc circumferential extension, and presence of optical coherence tomography (OCT)-defined macrophages] as detected by OCT. Composite of cardiac death and target segment myocardial infarction was the primary clinical endpoint. Methods and results From January 2013 to December 2016, 1003 patients undergoing OCT evaluation of the untreated proximal left anterior descending coronary artery in the context of clinically indicated coronary angiogram were prospectively enrolled at 11 independent centres (clinicaltrial.gov identifier NCT02883088). At 1-year, the primary clinical endpoint was observed in 37 patients (3.7%). In a total of 1776 lipid plaques, presence of MLA 180° (HR 2.4, 95% CI 1.2–4.8), and OCT-defined macrophages (HR 2.7, 95% CI 1.2–6.1) were all associated with increased risk of the primary endpoint. The pre-specified combination of plaque features (simultaneous presence of the four OCT criteria in the same plaque) was observed in 18.9% of patients experiencing the primary endpoint and was an independent predictor of events (HR 7.54, 95% CI 3.1–18.6). Conclusion The simultaneous presence of four high-risk OCT plaque features was found to be associated with a higher risk of major coronary events