Abstract
The increasing capabilities of smartphones is paving way to novel applications through the crowd-sourcing of these untapped resources, to form hyperlocal meshes commonly known as edge-clouds. While a relevant body-of-work is already available for the underlying networking, computing and storage facilities, security and privacy remain second class citizens. In this paper we present Panoptic, an edge-cloud system that enables the search for missing people, similar to the commonly known Amber alert system, in high density scenarios where wireless infrastructure might be limited (WiFi and LTE), e.g. concerts, while featuring privacy and security by design. Since the limited resources present in the mobile devices, namely battery capacity, Panoptic offers a computing offloading that tries to minimize data leakage while offering acceptable levels of performance. Our results show that it is achievable to run these algorithms in an edge-cloud configuration and that it is beneficial to use this architecture to lower data transfer through the wireless infrastructure while enforcing privacy. Results from our experimental evaluation show that the security layer does not impose a significant overhead, and only accounts for 2% of the total execution time for an edge cloud comprised by, but not limited to, 8 devices.

Abstract

Abstract
This paper presents an extensive analysis in relation to transforming electric distribution networks in order to accommodate large quantities of variable renewable energy sources (vRESs). For this purpose, a multi-stage and stochastic mixed integer linear programming (S-MILP) model is employed. The algebraic model developed optimally allocates energy storage systems (ESSs) along with an optimal dynamic distribution network switching. For the analysis, a standard IEEE 119-bus distribution network system was used as a case study. Test results reveal that the joint optimization of ESSs and network reconfiguration markedly increase flexibility in existing systems, leading to an increase in the levels of renewables integration and utilization. Moreover, the analysis of the results shows the prospect of such systems in going fully "carbonfree", i.e. with vRES power entirely meeting system demand. Generally, the current work demonstrates that a more effective integration and utilization of large-scale vRESs is possible when existing systems are equipped with enabling technologies that are already commercially available.

Abstract
Manaus, a city of more than two million people, suffers problems arising from strong sunlight and aggravated by several factors, such as traffic congestion and greenhouse gas emissions generated by evaporation and burning of fuel. The present study examined Carbon Monoxide (CO) and Nitrogen Dioxide (NO2) emissions in an urban area of the city using different methodologies. CO and NO2 were measured using automated and passive analyzers, respectively. Meanwhile, direct monitoring of these pollutants was performed in vehicular sources in the vicinity of sampling locations. Results showed that levels of carbon monoxide vary over time, being higher during peak movement of vehicles. NO2 values have exceeded the recommendations of the World Health Organization (WHO), and monitoring at source showed high levels of CO and NO2 emissions to the atmosphere.

Abstract
This note, reporting the homonym keynote presented in the International Symposium on Molecular Logic and Computational Synthetic Biology 2018, traces an informal roadmap on Dynamic Logic (DL) field, focusing on its versatility and resilience to be adjusted and adopted in a wide class of application domains and computational paradigms. The exposition argues the room for developments on tagging DL to the analysis of synthetic biologic domain. © 2019, Springer Nature Switzerland AG.

Abstract
This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces the so-called smart grid. We start by providing an overview of the recent research related to smart grid optimization. From the variety of challenges that arise in a smart grid context, we analyze with a significance importance the energy resource management problem since it is seen as one of the most complex and challenging in recent research. The survey also provides a discussion on the application of computational intelligence, with a strong emphasis on evolutionary computation techniques, to solve complex problems where traditional approaches usually fail. The last part of this survey is devoted to research on large-scale simulation towards applications in electricity markets and smart grids. The survey concludes that the study of the integration of distributed renewable generation, demand response, electric vehicles, or even aggregators in the electricity market is still very poor. Besides, adequate models and tools to address uncertainty in energy scheduling solutions are crucial to deal with new resources such as electric vehicles or renewable generation. Computational intelligence can provide a significant advantage over traditional tools to address these complex problems. In addition, supercomputers or parallelism opens a window to refine the application of these new techniques. However, such technologies and approaches still need to mature to be the preferred choice in the power systems field. In summary, this survey provides a full perspective on the evolution and complexity of power systems as well as advanced computational tools, such as computational intelligence and simulation, while motivating new research avenues to cover gaps that need to be addressed in the coming years.