Abstract

Abstract

Abstract
Several algorithms for clustering data streams based on k-Means have been proposed in the literature. However, most of them assume that the number of clusters, k, is known a priori by the user and can be kept fixed throughout the data analySis process. Besides the difficulty in choosing k, data stream clustering imposes several challenges to be addressed, such as addressing non-stationary, unbounded data that arrive in an online fashion. In this paper, we propose a Fast Evolutionary Algorithm for Clustering data streams (FEAC-Stream) that allows estimating k automatically from data in an online fashion. FEAC-Stream uses the Page-Hinkley Test to detect eventual degradation in the quality of the induced clusters, thereby triggering an evolutionary algorithm that re-estimates k accordingly. FEAC-Stream relies on the assumption that clusters of (partially unknown) data can provide useful information about the dynamics of the data stream. We illustrate the potential of FEAC-Stream in a set of experiments using both synthetic and real-world data streams, comparing it to four related algorithms, namely: CluStream-OMRk, CluStream-BkM, StreamKM++-OMRk and StreamKM++-BkM. The obtained results show that FEAC-Stream provides good data partitions and that it can detect, and accordingly react to, data changes.

Abstract
This paper presents a home area network (HAN)-based domestic load energy consumption monitoring prototype device as part of an advanced metering system (AMS). This device can be placed on individual loads or configured to measure several loads as a whole. The wireless communication infrastructure is supported on IEEE 805.12.04 radios that run a ZigBee stack. Data acquisition concerning load energy transit is processed in real time and the main electrical parameters are then transmitted through a RF link to a wireless terminal unit, which works as a data logger and as a human-machine interface. Voltage and current sensing are implemented using Hall effect principle-based transducers, while C code is developed on two 16/32-bit microcontroller units (MCUs). The main features and design options are then thoroughly discussed. The main contribution of this paper is that the proposed metering system measures the reactive energy component through the Hilbert transform for low cost measuring device systems.

Abstract
The use of augmented reality has a great potential applied to several areas, in particular, for cultural heritage context where it became possible to display, in loco, virtual elements which complement the user's real scenario. Due to technological advances, differentiated ways of experience this technology has been explored, providing to common user, the access to this technology, until recently, quite limited, especially, in public locations. This article presents a work which includes implementation and evaluation of distinct applications of augmented reality - using smartphones - based on different techniques and tools. The evaluation intends to identify a solution to be implemented in a cultural heritage context, namely, the ruins of the Museu Monografico de Conimbriga

Abstract
There are many open issues and challenges in the reinforcement learning field, such as handling high-dimensional environments. Function approximators, such as deep neural networks, have been successfully used in both single- and multi-agent environments with high dimensional state-spaces. The multi-agent learning paradigm faces even more problems, due to the effect of several agents learning simultaneously in the environment. One of its main concerns is how to learn mixed policies that prevent opponents from exploring them in competitive environments, achieving a Nash equilibrium. We propose an extension of several algorithms able to achieve Nash equilibriums in single-state games to the deep-learning paradigm. We compare their deep-learning and table-based implementations, and demonstrate how WPL is able to achieve an equilibrium strategy in a complex environment, where agents must find each other in an infinite-state game and play a modified version of the Rock Paper Scissors game. © Springer International Publishing AG 2018.