Abstract
In this paper, an angular frequency dynamic-based control technique is proposed to control interfaced converters between the power grid and renewable energy sources. The proposed control technique can guarantee a stable operation of power grid under high penetration of renewable energy resources through providing the required inertia properties. The synchronous generator characteristics combined with the basic dynamic model of the interfaced converter can shape a second order derivative of the grid angular frequency consisting of converter power and virtual mechanical power derivative with embedded virtual inertia to prevent instability from the power grid as well as to generate active and reactive power with appropriate inertia. Simulation analyses are performed in Matlab/Simulink to attest the high performance of the proposed control technique.

Abstract
Image dehazing deals with the removal of undesired loss of visibility in outdoor images due to the presence of fog. Retinex is a color vision model mimicking the ability of the Human Visual System to robustly discount varying illuminations when observing a scene under different spectral lighting conditions. Retinex has been widely explored in the computer vision literature for image enhancement and other related tasks. While these two problems are apparently unrelated, the goal of this work is to show that they can be connected by a simple linear relationship. Specifically, most Retinex-based algorithms have the characteristic feature of always increasing image brightness, which turns them into ideal candidates for effective image dehazing by directly applying Retinex to a hazy image whose intensities have been inverted. In this paper, we give theoretical proof that Retinex on inverted intensities is a solution to the image dehazing problem. Comprehensive qualitative and quantitative results indicate that several classical and modern implementations of Retinex can be transformed into competing image dehazing algorithms performing on pair with more complex fog removal methods, and can overcome some of the main challenges associated with this problem.

Abstract

Abstract
Home Health Care (HHC) services are growing worldwide and, usually, the home care visits are manually planned, being a time and effort consuming task that leads to a non optimized solution. The use of some optimization techniques can significantly improve the quality of the scheduling solutions, but lacks the achievement of solutions that face the fast reaction to condition changes. In such stochastic and very volatile environments, the fast re-scheduling is crucial to maintain the system in operation. Taking advantage of the inherent distributed and intelligent characteristics of Multi-agent Systems (MAS), this paper introduces a methodology that combines the optimization features provided by centralized scheduling algorithms, e.g. genetic algorithms, with the responsiveness features provided by MAS solutions. The proposed approach was codified in Matlab and NetLogo and applied to a real-world HHC case study. The experimental results showed a significant improvement in the quality of scheduling solutions, as well as in the responsiveness to achieve those solutions. © 2018, Springer International Publishing AG, part of Springer Nature.

Abstract
There is a set of important selection criteria in the design of fiber optic sensors that determine the compromise between design complexity and performance. Optical fiber sensors not only withstand high temperatures, but they can also operate in different chemical and aqueous media allowing measurements in areas not otherwise accessible. A Fabry-Perot cavity based on an air bubble created in a multimode fiber section is proposed. The air bubble is formed using only cleaving and fusion splicing techniques. The parameters used to produce the microcavities were found empirically. Two different configurations are explored: an inline cavity formed between two sections of MMF, and a fiber tip sensor. In the last, after the air bubble is created, a cleave is made near the cavity, after which the sensor is subjected to several electrical arcs to reshape the cavity and obtain a thin diaphragm. The inline sensor, with a length of similar to 297 mu m, was used to measure strain and presented a sensitivity of 6.48 pm/mu epsilon. Regarding the fiber tip sensor, it was subjected to glycerin/water mixture variations, by immerging the sensing head in several solutions with different concentrations of water in glycerin. In this case, the sensor had a length of similar to 167 mu m and a diaphragm thickness of similar to 20 mu m. As expected, with the increase of the external medium refractive index, the sensor visibility decreased. Furthermore, a wavelength shift towards red was observed, with a sensitivity of 7.81 pm/%wt. Both devices exhibited low dependence to temperature (<1.8 pm/degrees C).

Abstract
Estimation of strain in tendons for tendinopathy assessment is a hot topic within the sports medicine community. It is believed that, if accurately estimated, existing treatment and rehabilitation protocols can be improved and presymptomatic abnormalities can be detected earlier. State-of-the-art studies present inaccurate and highly variable strain estimates, leaving this problem without solution. Out-of-plane motion, present when acquiring two-dimensional (2D) ultrasound (US) images, is a known problem and may be responsible for such errors. This work investigates the benefit of high-frequency, three-dimensional (3D) US imaging to reduce errors in tendon strain estimation. Volumetric US images were acquired in silico, in vitro, and ex vivo using an innovative acquisition approach that combines the acquisition of 2D high-frequency US images with a mechanical guided system. An affine image registration method was used to estimate global strain. 3D strain estimates were then compared with ground-truth values and with 2D strain estimates. The obtained results for in silico data showed a mean absolute error (MAE) of 0.07%, 0.05%, and 0.27% for 3D estimates along axial, lateral direction, and elevation direction and a respective MAE of 0.21% and 0.29% for 2D strain estimates. Although 3D could outperform 2D, this does not occur in in vitro and ex vivo settings, likely due to 3D acquisition artifacts. Comparison against the state-of-the-art methods showed competitive results. The proposed work shows that 3D strain estimates are more accurate than 2D estimates but acquisition of appropriate 3D US images remains a challenge.