Abstract
This paper presents a synchronous resonant control strategy based on the inherent characteristics of permanent magnet synchronous generators (PMSG) for the control of power converters to provide stable operating conditions for the power grid under high penetration of renewable energy resources (RERs). The proposed control technique is based on the small signal linearization of a dynamic model with grid specifications, load-current-based voltages, and power converter currents. A combination of the linearized dynamic model with the PMSG swing equation and resonant controller leads to a control technique with synchronous features and appropriate inertia for the control of converter-based power generators. As the main contribution of this work, an extra functionality is proposed in the control loop of the proposed model to solve the inherent inconveniences of conventional synchronous generators. Also, a comprehensive collaboration between interfaced converter specifications and PMSG features is achieved as another contribution of the proposed control technique, and this can guarantee accurate performance under various conditions. A current perturbation curve is introduced to assess the variations of the grid frequency and voltage magnitude under operation of the interfaced converters controlled by the proposed control technique. Moreover, by taking into account the load-based voltages, the effects of the current perturbation components are investigated. The proposed model is simulated in MATLAB/Simulink environment to verify the high performance of the proposed control technique over the other existing control methods.

Abstract
The integration of functional imaging modality provided by Positron Emission Tomography (PET) and associated anatomical imaging modality provided by Computed Tomography (CT) has become an essential procedure both in the evaluation of different types of malignancy and in radiotherapy planning. The alignment of these two exams is thus of great importance. In this research work, three registration approaches (1) intensity-based registration, (2) rigid translation followed by intensity-based registration and (3) coarse registration followed by fine-tuning were evaluated and compared. To characterize the performance of these methods, 161 real volume scans from patients involved in Hodgkin Lymphoma staging were used: CT volumes used for radiotherapy planning were registered with PET volumes before any treatment. Registration results achieved 78%, 60%, and 91% of accuracy for methods (1), (2) and (3), respectively. Registration methods validation was extended to a corresponding landmarks points distance calculation. Methods (1), (2) and (3) achieved a median improvement registration rate of 66% mm, 51% mm and 70% mm, respectively. The accuracy of the proposed methods was further confirmed by extending our experiments to other multimodal datasets and in a monomodal dataset with different acquisition conditions.

Abstract
Shack-Hartmann wavefront sensing relies on accurate spot centre measurement. Several algorithms were developed with this aim, mostly focused on precision, i.e. minimizing random errors. In the solar and extended scene community, the importance of the accuracy (bias error due to peak-locking, quantization, or sampling) of the centroid determination was identified and solutions proposed. But these solutions only allow partial bias corrections. To date, no systematic study of the bias error was conducted. This article bridges the gap by quantifying the bias error for different correlation peak-finding algorithms and types of sub-aperture images and by proposing a practical solution to minimize its effects. Four classes of sub-aperture images (point source, elongated laser guide star, crowded field, and solar extended scene) together with five types of peak-finding algorithms (1D parabola, the centre of gravity, Gaussian, 2D quadratic polynomial, and pyramid) are considered, in a variety of signal-to-noise conditions. The best performing peak-finding algorithm depends on the sub-aperture image type, but none is satisfactory to both bias and random errors. A practical solution is proposed that relies on the antisymmetric response of the bias to the sub-pixel position of the true centre. The solution decreases the bias by a factor of similar to 7 to values of less than or similar to 0.02 pix. The computational cost is typically twice of current cross-correlation algorithms.

Abstract
Sharing location data is becoming more popular as mobile devices become ubiquitous. Location-based service providers use this type of data to provide geographically contextualized services to their users. However, sharing exact locations with possibly untrustworthy entities poses a thread to privacy. Geo-indistinguishability has been recently proposed as a formal notion based on the concept of differential privacy to design location privacy-preserving mechanisms in the context of sporadic release of location data. While adaptations for the case of continuous location updates have been proposed, the study on how the frequency of updates impacts the privacy and utility level is yet to be made. In this paper we address this issue, by analyzing the effect of frequency updates on the privacy and utility levels of four mechanisms: the standard planar Laplacian mechanism suitable for sparse locations, and three variants of an adaptive mechanism that is an adaptation of the standard mechanism for continuous location updates. Results show that the frequency of updates largely impacts the correlation between points. As the frequency of updates decreases, the correlation also decreases. The adaptive mechanism is able to adjust the privacy and utility levels accordingly to the correlation between past positions and current position. However, the estimator function that is used to predict the current location has a great influence in the obtained results.

Abstract
The design of fluorescent molecules with structural features for efficient immobilization in polymeric supports or binding matrixes is an active research topic, which aims to create materials with optical and mechanical properties suitable for sensing applications. Herein, we describe the synthesis and characterization of two new fluorescent ligands prepared by a combination of a rosamine platform and an isophthalate receptor using amine and amide linkages. In order to evaluate their potential application as fluorescence sensors, the photophysical properties of the ligands were accessed by UV-Vis and photoluminescence measurements in solution and after immobilization (infiltrated in TiO2 thin films). Furthermore, molecular and electronic structures of both ligands were rationalized by DFT and TD-DFT calculations. Interesting features were found for the ligand containing an amide bond, which has shown to be less prone to aggregation and has higher emission capacity, being a promising candidate in fluorescence sensor devices.

Abstract
In the later stages of the aging process, an elderly person might need the help of a family member or a caregiver. Technology can be used to help to take care of elderly persons. Autonomous systems, using special interfaces, can collect information from elderly people, which might be useful to predict and recognize health related problems or physical security problems in real time. The emerging technology of image processing, in particular, the emotion recognition, can be a good option to use in elderly care support systems. In this article, we implemented a Microsoft Azure – Emotion SDK to recognize emotion of elderly that able to detect faces and recognize emotions in real time and to be used for elderly care support. The analysis is done with an online video stream, which analyzes facial expression, so that in case of a critical emotion, e.g., if an elderly is very sad or crying, it will inform a caregiver or related entity. From the experiment, we concluded that emotion recognition is a reliable technology to be implemented in real time elderly care. © Springer International Publishing AG, part of Springer Nature 2018.