Abstract
This paper provides an overview of the expected role that variable speed hydro power plants can have in future electric power systems characterized by a massive integration of highly variable sources. Therefore, it is discussed the development of a methodology for optimising the operation of hydropower plants under increasing contribution from new renewable energy sources, addressing the participation of a hydropower plant with variable speed pumping in reserve markets. Complementarily, it is also discussed the active role variable speed generators can have in the provision of advanced frequency regulation services.

Abstract
' In this paper, a market-based control scheme is proposed to determine the minimum billing cost of responsive demands with the minimum impact on their satisfaction. For this purpose, the responsive demands are modeled as agents who bid to the energy market. In the model, the financial compensation provided by the market motivates the responsive demands to shift their load to off-peak periods. Since dissatisfaction is caused by the deviation from the reference consumption, the responsive demands' bids are dependent on the level of satisfaction that consumers are willing to have. Numerical results reveal that the billing cost of these customers is meaningfully decreased compared to the uncontrolled approaches. In addition, the results are compared to the centralized aggregation-based approach, in which a demand response aggregation entity directly buys energy on behalf of responsive demands in the market. The results indicate the effectiveness of the proposed decentralized market-based scheme.

Abstract
In this work a numerical model related to an optical inclinometer is presented. This model is based on a fused fiber taper monitored in the transmitted power. Comparisons are made between the numerical and experimental results and it is demonstrated good agreement with them. Thus, the model is proven to be suitable to simulate variation of parameters in order to obtain better performance of the sensor response. The numerical results demonstrate that is possible to enhance the inclinometer sensitivity by varying the legnth and waist of the taper. It is obtained a sensitivity of about 0,7 dB/degree using a taper length and waist of 1200 mu m and 30 mu m, respectively, at an angular range of 35 to 45 degrees.

Abstract
Given a retinal image, can we automatically determine whether it is of high quality (suitable for medical diagnosis)? Can we also explain our decision, pinpointing the region or regions that led to our decision? Images from human retinas are vital for the diagnosis of multiple health issues, like hypertension, diabetes, and Alzheimer's; low quality images may force the patient to come back again for a second scanning, wasting time and possibly delaying treatment. However, existing retinal image quality assessment methods are either black boxes without explanations of the results or depend heavily on feature engineering or on complex and error-prone anatomical structures' segmentation. Therefore, we propose EyeQual, that solves exactly this problem. EyeQual is novel, fast for inference, accurate and explainable, pinpointing low-quality regions on the image. We evaluated EyeQual on two real datasets where it achieved 100% accuracy taking just 36 milliseconds for each image.

Abstract
Clustering is a powerful and versatile tool for knowledge discovery, able to provide a valuable information for data analysis in various domains. To perform this task based on streaming data is quite challenging: outdated knowledge needs to be disposed while the current knowledge is obtained from fresh data; since data are continuously flowing, strict efficiency constraints have to be met. This paper presents WCDS, an approach to this problem based on the WiSARD artificial neural network model. This model already had useful characteristics as inherent incremental learning capability and patent functioning speed. These were combined with novel features as an adaptive countermeasure to cluster imbalance, a mechanism to discard expired data, and offline clustering based on a pairwise similarity measure for WiSARD discriminators. In an insightful experimental evaluation, the proposed system had an excellent performance according to multiple quality standards. This supports its applicability for the analysis of data streams.

Abstract
Jasmin is a framework for developing high-speed and high-assurance cryptographic software. The framework is structured around the Jasmin programming language and its compiler. The language is designed for enhancing portability of programs and for simplifying verification tasks. The compiler is designed to achieve predictability and efficiency of the output code (currently limited to x64 platforms), and is formally verified in the Coq proof assistant. Using the SUPER COP framework, we evaluate the Jasmin compiler on representative cryptographic routines and conclude that the code generated by the compiler is as efficient as fast, hand-crafted, implementations. Moreover, the framework includes highly automated tools for proving memory safety and constant-time security (for protecting against cache-based timing attacks). We also demonstrate the effectiveness of the verification tools on a large set of cryptographic routines.