Abstract
Time series data is composed of observations of one or more variables along a time period. By analyzing the variability of the variables we can reveal patterns that repeat or that are correlated, which helps to understand the behaviour of the variables over time. Our method finds frequent distributions of a target variable in time series data and discovers relationships between frequent distributions in consecutive time intervals. The frequent distributions are found using a new method, and relationships between them are found using association rules mining.

Abstract
Formal modeling and automatic analysis are essential to achieve a trustworthy software design prior to its implementation. Alloy and its Analyzer are a popular language and tool for this task. Frequently, rather than a single software artifact, the goal is to develop a full software product line (SPL) with many variants supporting different features. Ideally, software design languages and tools should provide support for analyzing all such variants (e.g., by helping pinpoint combinations of features that could break a property), but that is not currently the case. Even when developing a single artifact, support for multi-variant analysis is desirable to explore design alternatives. Several techniques have been proposed to simplify the implementation of SPLs. One such technique is to use background colors to identify the fragments of code associated with each feature. In this paper we propose to use that same technique for formal design, showing how to add support for features and background colors to Alloy and its Analyzer, thus easing the analysis of software design variants. Some illustrative examples and evaluation results are presented, showing the benefits and efficiency of the implemented technique. © Springer Nature Switzerland AG 2019.

Abstract
Autonomous Unmanned Aerial Vehicles (UAVs) become an important field of research in which multiple applications can be designed, such as surveillance, deliveries, and others. Thus, studies aiming to improve the performance of these vehicles are being proposed: from new sensing solutions to more robust control techniques. Additionally, the autonomous UAV has challenges in flight stages as the landing. This procedure needs to be performed safely with a reduced error margin in static and dynamic targets. To solve this imperative issue, many applications with computer vision and control theory have been developed. Therefore, this paper presents an alternative method to train a multilayer perceptron neural network based on fuzzy Mamdani logic to control the landing of a UAV on an artificial marker. The advantage of this method is the reduction in computational complexity while maintaining the characteristics and intelligence of the fuzzy logic controller. Results are presented with simulation and real tests for static and dynamic landing spots. For the real experiments, a quadcopter with an onboard computer and ROS is used.

Abstract
The exploration of water bodies from the sea to land filled water spaces has seen a continuous increase with new technologies such as robotics. Underwater images is one of the main sensor resources used but suffer from added problems due to the environment. Multiple methods and techniques have provided a way to correct the color, clear the poor quality and enhance the features. In this paper, we present the work of an Image Cleaning and Enhancement Technique which is based on performing color correction on images incorporated with Dark Channel Prior(DCP) and then taking the converted images and modifying them into the Long, Medium and Short(LMS) color space, as this space is the region in which the human eye perceives colour. This work is being developed at INESC TEC robotics and autonomous systems laboratory. Our objective is to improve the quality of images for and taken by robots with the particular emphasis on underwater flooded mines. The paper describes the architecture and the developed solution. A comparative analysis with state of the art methods and of our proposed solution is presented. Results from missions taken by the robot in operational mine scenarios are presented and discussed and allowing for the solution characterization and validation.

Abstract
The present study seeks to analyze the behavior of a technological start-up regarding its entry modes in foreign markets. It is based on the case study of a company in the field of 3D printing and takes into account the analysis of topics such as the internationalization of start-ups and modes of entry in foreign markets, considering several theories of internationalization. As the company analyzed is a start-up, the research is supported by the analysis of the characteristics present in the process of internationalization of small and medium-sized enterprises (SMEs). The study closes with the conclusion that this SME matches the profile of an International New Venture/Born Global (INV/BG), although the company takes advantage of the network-based theory and relationship orientation to enter international markets. The most used mode of entry by the company in international markets has been exporting activities.

Abstract
This paper represents a model for finding the strategic bidding equilibrium of a virtual power plant in a joint energy and regulation market in the presence of rivals. A bi-level mathematical program with equilibrium constraints (MPEC) is represented for modeling the behavior of each producer. The upper level deals with profit maximization of each strategic unit and the lower level encompasses social welfare maximization. This is the first objective of the presented model. Power transfer distribution factors (PTDFs) are employed to model transmission constraints. The proposed bi-level problem is converted to a traceable mixed integer linear programming problem using duality theory and Karush-Kahn-Tucker (KKT) optimization conditions. Simultaneous solution of all MPECs forms an equilibrium problem with equilibrium constraints (EPEC). Solving the resulting EPEC using diagonalization algorithm and game theory, a market Nash equilibrium is obtained. Another goal is to solve the bi-level problem in a bi-objective way using the augmented epsilon constraint method, which maximizes the profit and minimizes the emissions of virtual power plant units. The proposed model is tested on a standard IEEE-24 bus system and the results indicate that, at the equilibrium point, the profit of a virtual power plant and GenCo will be less than in the initial state.