Abstract
In this study, a direct load control strategy for procuring flexibility from residential heating, ventilation, and air conditioning (HVAC) units and the optimal management of shared energy storage systems connected at different buses of a distribution system is proposed, as a new contribution with respect to earlier studies, aiming to minimize the energy demand during DR event periods. Moreover, an additional objective related to the minimization of the end-users' discomfort induced by the interruption of the HVAC units is considered, leading to the formulation of a bi-level optimization problem based on a second-order conic programming representation of the AC power flow equations. The effectiveness of the proposed methodology is demonstrated by performing simulations on a test system and comparisons with other approaches.

Abstract
Supply chains have become one of the most important strategic themes in the aerospace industry in recent years as globalization and deep technological changes have altered the industry at many levels, creating new dynamics and strategies. In this setting, sustainability at the supply chain level is an emerging research topic, whose contributions aim to support businesses into the future. To do so the development of new products and the response to new industry requirements, while incorporating new materials appears as a path to follow, which require more resilient and agile supply chains, while guaranteeing their sustainability. Such supply chains will be better prepared for the future complex challenges and risks faced by the aerospace companies. Such challenges are addressed in this work, where an integrated framework is proposed to contribute to the resilience and sustainability of aerospace supply chains. Using different analysis methods, the framework addresses four important challenges in the context of aerospace supply chain sustainability: evolution and new trends, performance assessment, supplier selection, and supply chain design and planning. © 2019, Springer Nature Switzerland AG.

Abstract
We present PEPITO as a new low-cost and low-complexity concept for profiling the vertical distribution of atmospheric turbulence. PEPITO utilizes post facto tip-tilt (TT) corrected short-exposure images to reproduce the anisokinetism effect and then produces the profile estimation using a model-fitting algorithm. We present in this proceedings the methodology we use to estimate the profile and simulation results, that show that PEPITO can reach potentially 1% of accuracy on a 0.5 m telescope by using 5 stars of magnitude mV=15 mag and distributed over a field of 10, arcmin. We present the sensitivity of PEPITO as well as a sky coverage analysis.

Abstract
Denial of Service attacks, which have become commonplace on the Information and Communications Technologies domain, constitute a class of threats whose main objective is to degrade or disable a service or functionality on a target. The increasing reliance of Cyber-Physical Systems upon these technologies, together with their progressive interconnection with other infrastructure and/or organizational domains, has contributed to increase their exposure to these attacks, with potentially catastrophic consequences. Despite the potential impact of such attacks, the lack of generality regarding the related works in the attack prevention and detection fields has prevented its application in real-world scenarios. This paper aims at reducing that effect by analyzing the behavior of classification algorithms with different dataset characteristics.

Abstract
We propose a coding methodology for physical layer security with adaptive characteristics, whereby adaptive we mean that the system must be tunable to different operational points/signal-to-noise ratio levels of both the legitimate receiver and the eavesdropper. Based on interleaving and scrambling as techniques that shuffle the original message before transmission, we consider puncturing over an interleaving/scrambling key and/or over the message as a mechanism to provide the required adaptability to channel conditions. The proposed techniques have shown suitable adaptability to different channel quality levels of the legitimate receiver and eavesdropper, while still guaranteeing the desired reliability for the legitimate receiver and secrecy against the eavesdropper.

Abstract
In this paper, we present the BeamSouL sequence miner that finds sequences of logical atoms. This algorithm uses a levelwise hybrid search strategy to find a subset of contrasting logical sequences available in a SeqLog database. The hybrid search strategy runs an exhaustive search, in the first phase, followed by a beam search strategy. In the beam search phase, the algorithm uses the confidence metric to select the top k sequential patterns that will be specialized in the next level. Moreover, we develop a first-order logic classification framework that uses predicate invention technique to include the BeamSouL findings in the learning process. We evaluate the performance of our proposals using four multi-relational databases. The results are promising, and the BeamSouL algorithm can be more than one order of magnitude faster than the baseline and can find long and highly discriminative contrasting sequences.