Abstract
Focused ion beam technology is combined with dynamic chemical etching to create microcavities in tapered optical fiber tips, resulting in fiber probes for temperature and refractive index sensing. Dynamic chemical etching uses hydrofluoric acid and a syringe pump to etch standard optical fibers into cone structures called tapered fiber tips where the length, shape, and cone angle can be precisely controlled. On these tips, focused ion beam is used to mill several different types of Fabry-Perot microcavities. Two main cavity types are initially compared and then combined to form a third, complex cavity structure. In the first case, a gap is milled on the tapered fiber tip which allows the external medium to penetrate the light guiding region and thus presents sensitivity to external refractive index changes. In the second, two slots that function as mirrors are milled on the tip creating a silica cavity that is only sensitive to temperature changes. Finally, both cavities are combined on a single tapered fiber tip, resulting in a multi-cavity structure capable of discriminating between temperature and refractive index variations. This dual characterization is performed with the aid of a fast Fourier transform method to separate the contributions of each cavity and thus of temperature and refractive index. Ultimately, a tapered optical fiber tip probe with sub-standard dimensions containing a multi-cavity structure is projected, fabricated, characterized and applied as a sensing element for simultaneous temperature and refractive index discrimination.

Abstract
Cyber-Physical Systems (CPSs) represent systems where computations are tightly coupled with the physical world, meaning that physical data is the core component that drives computation. Industrial automation systems, wireless sensor networks, mobile robots and vehicular networks are just a sample of cyber-physical systems. Typically, CPSs have limited computation and storage capabilities due to their tiny size and being embedded into larger systems. With the emergence of cloud computing and the Internet-of-Things (IoT), there are several new opportunities for these CPSs to extend their capabilities by taking advantage of the cloud resources in different ways. In this survey paper, we present an overview of research efforts on the integration of cyber-physical systems with cloud computing and categorize them into three areas: (1) remote brain, (2) big data manipulation, (3) and virtualization. In particular, we focus on three major CPSs namely mobile robots, wireless sensor networks and vehicular networks. © 2016 Elsevier B.V.

Abstract
This paper deals with the distribution network reconfiguration problem in a multi-objective scope, aiming to determine the optimal radial configuration by means of minimizing the active power losses and a set of commonly used reliability indices formulated with reference to the number of customers. The indices are developed in a way consistent with a mixed-integer linear programming (MILP) approach. A key contribution of the paper is the efficient implementation of the epsilon-constraint method using lexicographic optimization in order to solve the multi-objective optimization problem. After the Pareto efficient solution set is generated, the resulting configurations are evaluated using a backward/forward sweep load-flow algorithm to verify that the solutions obtained are both non-dominated and feasible. Since the epsilon-constraint method generates the Pareto front but does not incorporate decision maker (DM) preferences, a multi-attribute decision making procedure, namely, the technique for order preference by similarity to ideal solution (TOPSIS) method, is used in order to rank the obtained solutions according to the DM preferences, facilitating the final selection. The applicability of the proposed method is assessed on a classical test system and on a practical distribution system.

Abstract
With the advent of social networking, a lot of user-specific, voluntarily provided data has been generated. Researchers and companies noticed the value that lied within those enormous amounts of data and developed algorithms and tools to extract patterns in order to act on them. TweeProfiles is an offline clustering tool that analyses tweets over multiple dimensions: spatial, temporal, content and social. This project was extended in TweeProfiles2 by enabling the processing of real-time data. In this work, we developed a visualization tool suitable for data streaming, using multiple widgets to better represent all the information. The usefulness of the developed tool for journalism was evaluated based on a usability test, which despite its reduced number of participants yielded good results.

Abstract
Software development processes can generate significant amounts of data that can be periodically analyzed to identify performance problems, determine their root causes and devise improvement actions. However, conducting that analysis manually is challenging because of the potentially large amount of data to analyze and the effort and expertise required. ProcessPAIR is a novel tool designed to help developers analyze their performance data with less effort, by automatically identifying and ranking performance problems and potential root causes. The analysis is based on performance models derived from the performance data of a large community of developers. In this paper, we present the results of an experiment conducted in the context of Personal Software Process (PSP) training, to show that ProcessPAIR is able to accurately identify and rank performance problems and potential root causes of individual developers so that subsequent manual analysis for the identification of deeper causes and improvement actions can be properly focused.

Abstract
This paper presents the approach followed under project SENSIBLE to prove, in field-test scenarios, the benefits of integrating and coordinating small-scale storage devices to: (i) reduce the impact of Distributed Renewable Energy Sources in the Low Voltage grid and (ii) support the transition and the operation in islanding mode in the demonstration grid. The functional and ICT architecture developed for the Portuguese Demonstrator of Évora is presented, focusing in the use cases defined to test and validate the tools developed to enable the active management of the LV grid during both normal and islanded modes.