Abstract
Mobile device users have been growing in the last years but the limited battery life of these devices is considered one of the major issues amongst users and programmers. Therefore, there is a need to guide developers in developing mobile applications in the most energy efficient way. One of the ways to improve this is to provide live feedback about the energy efficiency of a program while it's being programmed. We have analyzed and compared a total of 16 different tools and presented a list of 15 code smells and respective refactorings. From the analyzed tools, Leafactor is the closest to a valid solution to our problem because it's the only energy-aware tool with the highest liveness level. However, in order to be executed the programmer needs to trigger it on the IDE by selecting the file, instead of automatically being executed without the programmer being noticed and refactor his inefficient code. © 2020 Owner/Author.

Abstract
Multiple real-world problems are naturally modeled as cooperative multi-agent systems, ranging from satellite formation to traffic monitoring. These systems require algorithms that can learn successful policies with independent agents that rely solely on local partial-observations of the environment. However, multi-agent environments are more complex, due to their partial-observability and non-stationarity from an agent's perspective, as well as the structural credit assignment problem and the curse of dimensionality, and achieving coordination in such systems remains a complex challenge. To this end, we propose a multi-agent actor-critic algorithm called Asynchronous Advantage Actor Centralized-Critic with Communication (A3C3). A3C3 uses a centralized critic to estimate a value function, decentralized actors to approximate each agent's policy function, and decentralized communication networks for each agent to share relevant information with its team. The critic can incorporate additional information, like the environment's global state, when available, and optimizes the actor networks. The actor networks of an agent's teammates optimize that agent's communication network, such that each agent learns to output information that is relevant to the policies of others. A3C3 supports a dynamic amount of agents, noisy communication mediums, and can be horizontally scaled to shorten its learning phase. We evaluate A3C3 in two partially-observable multi-agent suites where agents benefit from communicating local information to each other. A3C3 outperforms state-of-the-art multi-agent algorithms, independent approaches, and centralized controllers with access to all agents' observations.

Abstract
The characterization of wave transformation processes in the nearshore is of paramount importance when it comes to assessing storm and flooding impacts, sediment transportation and deposition, harbors safety or design of coastal protective structures. This study analyzes nonlinear wave parameters on Ofir sandy beach. This beach is located along the northwest Portuguese coast which is a highly energetic coast exposed to waves generated far away in the Atlantic Ocean. Despite the existence of rocky outcrops in the nearshore and intertidal zones at the study site, reducing the wave energy that reaches the beach, the study site exhibits pronounced erosive processes. Field observations of six near-bottom pressure records collected at the intertidal zone help to characterize the evolution of wave nonlinearities which are directly associated with sediment transport mechanisms. Data results show that there is an interrelation between the characteristics of the waves and the local morphology. It is also possible to ascertain, more clearly, the level of asymmetry present in the waves propagated at different depths, contributing to a better understanding of the local morpho-hydrodynamics.

Abstract
The integration of meta-knowledge on the Web of data is essential to support trustworthiness. This is in fact an issue because of the enormous amount of data that exists on the Web of Data. Meta-knowledge describes how the data is generated, manipulated, and disseminated. In the last few years, several approaches have been proposed for tracing and representing meta-knowledge efficiently on a statement or on a set of statements in the Semantic Web. The approaches differ significantly; for instance, in terms of modelling patterns, the number of statements generation, redundancy of the resources, query length, or query response time. This article reports a systematic review of the various approaches of the four dimensions (namely time, trust, fuzzy, and provenance) to provide an overview of the meta-knowledge assertion techniques in the field of the Semantic Web. Some experiments are conducted to analyze the actual performance of the approaches of meta-knowledge assertion considering the provenance dimension. These experiments are based on specific parameters such as graph size, number of statements generation, redundancy, query length, and query response time. All the experiments are done with real-world datasets. The semantics of the different approaches are compared to analyze the methodology of the approaches. Our study and experiments highlight the advantages and limitations of the approaches in terms of the parameters mentioned above.

Abstract
People that do not have access to the transport system and therefore, a facilitated access to goods and services essential to daily life, can be regarded as transport-related social excluded. This is a big issue, namely for groups of people that have physical, sensorial and/or cognitive limitations. This paper provides guidelines to design route planners for socially excluded groups, by promoting social inclusion in public transportation. For this purpose, a set of mock-up user-interfaces of an inclusive inter-modal route planning application were developed. These interfaces will deliver ready availability of information about infrastructures and other journey related data.

Abstract
Packing rings into a minimum number of rectangles is an optimization problem which appears naturally in the logistics operations of the tube industry. It encompasses two major difficulties, namely the positioning of rings in rectangles and the recursive packing of rings into other rings. This problem is known as the Recursive Circle Packing Problem (RCPP). We present the first dedicated method for solving RCPP that provides strong dual bounds based on an exact Dantzig-Wolfe reformulation of a nonconvex mixed-integer nonlinear programming formulation. The key idea of this reformulation is to break symmetry on each recursion level by enumerating one-level packings, i.e., packings of circles into other circles, and by dynamically generating packings of circles into rectangles. We use column generation techniques to design a "price-and-verify" algorithm that solves this reformulation to global optimality. Extensive computational experiments on a large test set show that our method not only computes tight dual bounds, but often produces primal solutions better than those computed by heuristics from the literature.