Abstract
The aim of this chapter is to present a domain model that represents the informational needs of transparency (governance structure and accountability dimensions) in Portuguese cooperatives. A domain model is an abstract representation of a reality and a milestone in the development of a metadata application profile (MAP). A community of practice publishes linked open MAP-based data for these data to be interoperable; this means intelligent software/agents can aggregate these data, provide different types of visualizations, infer from the data, and ultimately provide new discoveries. This model was developed having as basis the information obtained from the accomplishment of a focus group, and the analysis of financial reports and websites of seven Portuguese cooperatives. The authors will continue to work on the domain model to include 1) other dimensions that also contribute for transparency in the organizations and 2) other types of entities of the social economy (SE). The final aim is to define a model representing the needs of transparency of all types of European SE entities.

Abstract
In Multi-Label Stream Classification (MLSC) examples arriving in a stream can be simultaneously classified into multiple classes. This is a very challenging task, especially considering that new classes can emerge during the stream (Concept Evolution), and known classes can change over time (Concept Drift). In real situations, these characteristics come together with a scenario with Infinitely Delayed Labels, where we can never access the true class labels of the examples to update classifiers. In order to overcome these issues, this paper proposes a new method called MultI-label learNing Algorithm for Data Streams with Binary Relevance transformation (MINAS-BR). Our proposal uses a new Novelty Detection (ND) procedure to detect concept evolution and concept drift, being updated in an unsupervised fashion. We also propose a new methodology to evaluate MLSC methods in scenarios with Infinitely Delayed Labels. Experiments over synthetic data sets attested the potential of MINAS-BR, which was able to adapt to different concept drift and concept evolution scenarios, obtaining superior or competitive performances in comparison to literature baselines.

Abstract
The characterization of water and energy consumptions is essential in order to define strategies for their rational use. The way these resources are used in households is the path for efficient and rational management, interdependent from each other. It is believed that there are significant differences between the patterns of water and energy consumption in rural and urban areas, where influencing factors should also be identified. This article aims to provide some preliminary results of a research project named ENERWAT, with the main goal to characterize the relation between water and energy consumption at the end use level for urban and rural environments. One of the goals of the aforementioned project was the design, application, and results analysis of a survey, in order to find the main differences in the water and energy consumptions at the end use level and the factors that influence it in urban and rural households. A total of 245 households participated in the research during 2016 (110 urban dwellings and 135 rural), responding to questions on their family composition, dwellings characterization, water and energy consumption habits, and conservation behaviors of these resources. The project also includes the instrumentation and monitoring of dwellings in rural and urban environments to quantify the water consumption and related energy consumption. This stage is still in progress and includes in situ measurements of nine different households (four in rural and five in urban environments) during at least one year. In this article, some of the results obtained by the survey application and the in situ measurements are presented. Despite the large number of data and the associated complexity, it can be concluded that the joint analysis of the results allows identification of a connection between water and energy consumption, as well as a household’s consumption patterns.

Abstract
Mechanisation is a key input in modern agriculture, while it accounts for a large part of crop production costs, it can bring considerable farm benefits if well managed. Models for simulated machinery costs, may not replace actual cost measurements but the information obtained through them can replace a farm's existing records, becoming more valuable to decision makers. MACHoice, a decision support system (DSS) presented in this paper, is a farm machinery cost estimator and break-even analyzer of alternatives for agricultural operations, developed using user-driven expectations and in close collaboration with agronomists and computer engineers. It integrates an innovative algorithm developed for projections of machinery costs under different rates of annual machine use and work capacity processing, which is crucial to decisions on break-even machinery alternatives. A case study based on the comparison of multiple alternatives for grape harvesting operations is presented to demonstrate the typical results that can be expected from MACHoice, and to identify its capabilities and limitations. This DSS offers an integrated and flexible analysis environment with a user-friendly graphical interface as well as a high level of automation of processing chains. The DSS-output consists of charts and tables, evidencing the differences related to costs and carbon emissions between the options inserted by the user for the different intensity of yearly work proceeded. MACHoice is an interactive web-based tool that can be accessed freely for non-commercial use by every known browser.

Abstract
Performance of series connected batteries is limited by the "weakest link" effect, i.e., the cell or group of cells with the poorest performance in terms of temperature, power, or energy characteristics. To mitigate the "weakest link" effect, this study deals with the design, modeling, and experimental demonstration of a smart and hybrid balancing system (SHBS). A cell-to-cell shared energy transfer configuration is proposed, including a supercapacitor bank in the balancing bus, thus enabling hybridization. Energy is transferred from each battery module connected in series to the balancing bus, and vice-versa, by means of low-cost bi-directional dc-dc converters. The current setpoints of the converters are obtained by means of a smart balancing control strategy, implemented using convex optimization. The strategy is called "smart" because it pursues goals beyond the conventional state-of-charge equalization, including temperature and power capability equalization, and minimization of energy losses. Simulations show that the proposed SHBS is able to achieve all these goals effectively in an e-mobility application and are also used to assess the impact of different hybridization ratios and cooling conditions. Finally, an experimental setup is developed to demonstrate the feasibility of the SHBS.

Abstract
The health centers group (ACES) "Douro Sul II" is creating a Community Support Team for Palliative Care (ECSCP) to provide palliative care services for the ACE's population of 73, 713 registered users. To support these services, a study was carried out and it was planned the development of an Information System (IS) with the main objective of monitoring patients from their homes, providing information to support the operations of the team. The system is based on a platform that controls the flow of information between coordinators, team and the patients, from the use of mobile and web applications. Therefore, the team will be able to respond more quickly to patients requiring support.