Abstract
Optical modulation characteristics of resonant tunneling diode photodetectors (RTD-PD) are investigated. Intensity modulated light excites the RTD-PDs to conduct data experiments. Simple and complex data patterns are used with results showing data rates up to 80 and 200 Mbit/s, respectively. This is the first demonstration of complex modulation using resonant tunneling diodes.

Abstract
Smart Transformers (ST) are power-electronic based apparatuses that bring new opportunities for defining innovative operating strategies for Medium Voltage (MV) and Low Voltage (LV) distribution grids in future scenarios with increased shares of small-scale generation units. A distinctive advantage of ST is the possibility of connecting a storage device in the DC link when considering a three-stage configuration (AC/DC/AC). In this paper, ST is exploited within the context of Multi-Microgrids (MMG) in order to enhance the possibility of islanding operation through the identification of new control functionalities. The identification of robust control strategies to coordinate the flexibility of all the available resources (distributed resources at the LV and MV grids and storage units connected to the ST) is required to guarantee the successful operation of the MMG in the islanded mode. In order to address the need of specific control requirements, two different configurations are considered, being the proposed control strategies properly described: (1) ST with an energy storage unit in the DC link which fully decouples all the control possibilities for the MV and LV grid sides; (2) ST without an energy storage unit, requiring proper coordination between the MV and LV grid levels.

Abstract
Smartphones are increasingly present in human’s life. For example, for entertainment many people use their smartphones to watch videos or listen to music. Many users, however, stream or play videos with the intention to only listen to the audio track. This way, some battery energy, which is critical to most users, is unnecessarily consumed thus and switching between video and audio can increase the time of use of the smartphone between battery recharges. In this paper, we present a first approach that, based on the user context, can automatically switch between video and audio. A supervised learning approach is used along with the classifiers K-Nearest Neighbors, Hoeffding Trees and Naive Bayes, individually and combined to create an ensemble classifier. We investigate the accuracy for recognizing the context of the user and the overhead that this system can have on the smartphone energy consumption. We evaluate our approach with several usage scenarios and an average accuracy of 88.40% was obtained for the ensemble classifier. However, the actual overhead of the system on the smartphone energy consumption highlights the need for researching further optimizations and techniques. © 2019, Springer Nature Switzerland AG.

Abstract

Abstract
This work presents a neural network used to diagnosis patients with benign or malignant breast cancer. The study is carried out using the Breast Cancer Wisconsin dataset. To solve the problem a feedforward neural network (NN) with multilayers was used. In the work, the implementation was made in Python, using two different libraries (sklearn and keras). Experimental results were obtained by performing simulations in both developed applications, and the performance of the neural classifier was evaluated through the performance measures of the classification systems and the ROC curve. The results were promising, since the NN was able to discriminate with high accuracy the two separable sets discriminating the benign or malignant tumor patients.

Abstract
The purpose of this special issue is to assemble high quality papers that deepen and boost understanding the role of open innovation and knowledge on business ecosystems development. This special issue includes ten papers specific related to the special issue topic: Open Innovation and Knowledge for Fostering Business Ecosystems. Jointly, the papers scrutinize and explore this subject using different theoretical backgrounds and methodologies. Individually, each paper provides interesting insights concerning the singularities they explore. (C) 2018 Journal of Innovation & Knowledge. Published by Elsevier Espana, S.L.U.