University of Palermo

About: University of Palermo is a education organization based out in Palermo, Italy. It is known for research contribution in the topics: Population & Medicine. The organization has 15621 authors who have published 40250 publications receiving 964384 citations. The organization is also known as: Università degli Studi di Palermo & Universita degli Studi di Palermo.

Microgrid supervisory controllers and energy management systems: A literature review

Abstract: Microgrids (MGs), featured by distributed energy resources, consumption and storage, are designed to significantly enhance the self-sustainability of future electric distribution grids. In order to adapt to this new and revolutionary paradigm, it is necessary to control MGs in intelligent and coordinated fashion. To this aim, a new generation of advanced Microgrid Supervisory Controllers (MGSC) and Energy Management Systems (EMS) has emerged. The aim of this paper is to summarize the control objectives and development methodologies in the recently proposed MGSC/EMS. At first, a classification of control objectives is made according to the definition of hierarchical control layers in MGs. Then, focusing on MGSC/EMS related studies, a detailed methodology review is given with emphasis on representative applications and research works. Finally, the conclusions are summarized and the proposals of future research directions in this area are given.

Human Activity Recognition Process Using 3-D Posture Data

Abstract: In this paper, we present a method for recognizing human activities using information sensed by an RGB-D camera, namely the Microsoft Kinect. Our approach is based on the estimation of some relevant joints of the human body by means of the Kinect; three different machine learning techniques, i.e., K-means clustering, support vector machines, and hidden Markov models, are combined to detect the postures involved while performing an activity, to classify them, and to model each activity as a spatiotemporal evolution of known postures. Experiments were performed on Kinect Activity Recognition Dataset, a new dataset, and on CAD-60, a public dataset. Experimental results show that our solution outperforms four relevant works based on RGB-D image fusion , hierarchical Maximum Entropy Markov Model , Markov Random Fields , and Eigenjoints , respectively. The performance we achieved, i.e., precision/recall of 77.3% and 76.7%, and the ability to recognize the activities in real time show promise for applied use.

Symmetric Galerkin Boundary Element Methods

Abstract: This review article concerns a methodology for solving numerically, for engineering purposes, boundary and initial-boundary value problems by a peculiar approach characterized by the following features: the continuous formulation is centered on integral equations based on the combined use of single-layer and double-layer sources, so that the integral operator turns out to be symmetric with respect to a suitable bilinear form. The discretization is performed either on a variational basis or by a Galerkin weighted residual procedure, the interpolation and weight functions being chosen so that the variables in the approximate formulation are generalized variables in Prager’s sense. As main consequences of the above provisions, symmetry is exhibited by matrices with a key role in the algebraized versions; some quadratic forms have a clear energy meaning; variational properties characterize the solutions and other results, invalid in traditional boundary element methods enrich the theory underlying the computational applications. The present survey outlines recent theoretical and computational developments of the title methodology with particular reference to linear elasticity, elastoplasticity, fracture mechanics, time-dependent problems, variational approaches, singular integrals, approximation issues, sensitivity analysis, coupling of boundary and finite elements, and computer implementations. Areas and aspects which at present require further research are identified, and comparative assessments are attempted with respect to traditional boundary integral-elements. This article includes 176 references.

Comparison of US Strain Elastography and Entero-MRI to Typify the Mesenteric and Bowel Wall Changes during Crohn's Disease: A Pilot Study.

Abstract: Purpose. To evaluate and compare the mesenteric and bowel wall changes during Crohn’s disease (CD) on ultrasonography (US) Strain Elastography (SE) and Enterography Magnetic Resonance Imaging (E-MRI). Methods. From July 2014 to September 2016, 35 patients with ileocolonoscopy diagnosis of CD were prospectively examined with E-MRI and in the same time with US and SE. Results. A total of 41 affected bowel segments and 35 unaffected bowel segments in 35 patients were evaluated. US-SE color-scale coding showed a blue color pattern in the fibrotic mesentery and bowel wall in 15 patients and a green color pattern in the edematous ones in 20 patients. The signal of the bowel wall and mesenteric fat was iso/hypointense on T2-weighted sequence in the fibrotic pattern (23/35 and 12/35 patients) and hyperintense in the edematous pattern (12/35 and 23/35 patients). Mean ADC values were, respectively, 2, ,33 × 10−3 for the fibrotic mesentery and 2, ,28 × 10−3 for edematous one. There was a statistical correlation between US-SE color-scale and T2 signal intensity and between the US-SE color-scale and ADC maps. Conclusions. US-SE, ADC, and signal intensity on T2-weighted sequences on MR prove to be useful tools for the evaluation of CD pattern.