Abstract
The coefficient diagram method is primarily an algebraic control design method whose objective is to easily obtain a good controller with minimum user effort. As a matter of fact, if a system model, in the form of linear differential equations, is known, the user only need to define a time-constant and the controller order. The later can be established regarding the expected disturbance type via a lookup table first published by Koksal and Hamamci in 2004. However an inaccuracy in this table was detected and pointed-out in the present work. Moreover the above mentioned table was expanded in order to enclose any k order type disturbance

Abstract

Abstract
Current solutions for delivering adapted multimedia content in mobile environments take into account only a limited set of contextual information, and can be regarded as passive solutions. We propose a new solution that anticipates user's needs based on the contexts of use and preferences to deliver media content to mobile users. This paper describes the profiling approach of the proposed solution, and a context-aware content-based recommendation for smart devices. Recommendations are issued based on user history, driven by real-time contextual conditions.

Abstract
Penetration of distributed generation systems in conventional power systems leads to power quality (PQ) disturbances. This paper provides an improved PQ disturbances classification, which is associated with load changes and environmental factors. Various forms of PQ disturbances, including sag, swell, notch, and harmonics, are taken into account. Several features are obtained through hyperbolic S-transform, out of which the optimal features are selected using a genetic algorithm. These optimal features are used for PQ disturbances classification by employing support vector machines (SVMs) and decision tree (DT) classifiers. The study is supported by three different case studies, considering the experimental setup prototypes for wind energy and photovoltaic systems, as well as the modified Nordic 32-bus test system. The robustness and precision of DT and SWM are performed with noise and harmonics in the disturbance signals, thus providing comprehensive results.

Abstract
In this paper we explore a novel feature for the segmentation of heart sounds: the entropy gradient. We are motivated by the fact that auscultations in real environments are highly contaminated by noise and results reinforce our suspicions that the entropy gradient is not only robust to such noise but maintains a high sensitivity to the S1 and S2 components of the signal. Our whole approach consists of three stages, out of which the last two are novel contributions to this field. The first stage consists of typical pre-processing and wavelet reconstruction to obtain the Shannon energy envelogram. On the second stage we use an embedding matrix to track the dynamics of the system, which is formed by delay vectors with higher dimension than the corresponding attractor. On the third stage, we use the eigenvalues and eigenvectors of the embedding matrix to estimate the entropy of the envelogram. Finite differences are used to estimate entropy gradients, in which standard peak picking approaches are used for heart sound segmentation. Experiments are performed on a public dataset of pediatric auscultations obtained in real environments and results show the promising potential of this novel feature for such noisy scenarios.

Abstract