Advances in the Hierarchical Emergent Behaviors (HEB) approach to autonomous vehicles

Widespread deployment of autonomous vehicles (AVs) presents formidable challenges in terms on handling scalability and complexity, particularly regarding vehicular reaction in the face of unforeseen corner cases. Hierarchical Emergent Behaviors (HEB) is a scalable architecture based on the concepts of emergent behaviors and hierarchical decomposition. It relies on a few simple but powerful rules to govern local vehicular interactions. Rather than requiring prescriptive programming of every possible scenario, HEB’s approach relies on global behaviors induced by the application of these local, well-understood rules. Our first two papers on HEB focused on a primal set of rules applied at the first hierarchical level. On the path to systematize a solid design methodology, this paper proposes additional rules for the second level, studies through simulations the resultant richer set of emergent behaviors, and discusses the communica-tion mechanisms between the different levels.Peer ReviewedPostprint (author's final draft

The envelope of the power spectra of over a thousand \delta Scuti stars. The Tˉeff\bar{T}_{eff}-νmax\nu_{max} scaling relation

CoRoT and Kepler high-precision photometric data allowed the detection and characterization of the oscillation parameters in stars other than the Sun. Moreover, thanks to the scaling relations, it is possible to estimate masses and radii for thousands of solar-type oscillating stars. Recently, a \Delta\nu - \rho relation has been found for \delta Scuti stars. Now, analyzing several hundreds of this kind of stars observed with CoRoT and Kepler, we present an empiric relation between their frequency at maximum power of their oscillation spectra and their effective temperature. Such a relation can be explained with the help of the \kappa-mechanism and the observed dispersion of the residuals is compatible with they being caused by the gravity-darkening effect

Emergent behaviors in the Internet of things: The ultimate ultra-large-scale system

To reach its potential, the Internet of Things (IoT) must break down the silos that limit applications' interoperability and hinder their manageability. Doing so leads to the building of ultra-large-scale systems (ULSS) in several areas, including autonomous vehicles, smart cities, and smart grids. The scope of ULSS is both large and complex. Thus, the authors propose Hierarchical Emergent Behaviors (HEB), a paradigm that builds on the concepts of emergent behavior and hierarchical organization. Rather than explicitly programming all possible decisions in the vast space of ULSS scenarios, HEB relies on the emergent behaviors induced by local rules at each level of the hierarchy. The authors discuss the modifications to classical IoT architectures required by HEB, as well as the new challenges. They also illustrate the HEB concepts in reference to autonomous vehicles. This use case paves the way to the discussion of new lines of research.Damian Roca work was supported by a Doctoral Scholarship provided by Fundación La Caixa. This work has been supported by the Spanish Government (Severo Ochoa grants SEV2015-0493) and by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316-P).Peer ReviewedPostprint (author's final draft

Evidence of amplitude modulation due to Resonant Mode Coupling in the delta Scuti star KIC5892969

A study of the star KIC5892969 observed by the Kepler satellite is presented. Its three highest amplitude modes present a strong amplitude modulation. The aim of this work is to investigate amplitude variations in this star and their possible cause. Using the 4 years-long observations available, we obtained the frequency content of the full light curve. Then, we studied the amplitude and phase variations with time using shorter time stamps. The results obtained are compared with the predicted ones for resonant mode coupling of an unstable mode with lower frequency stable modes. Our conclusion is that resonant mode coupling is consistent as an amplitude limitation mechanism in several modes of KIC5892969 and we discuss to which extent it might play an important role for other delta Scuti stars

Evidence of chaotic modes in the analysis of four delta Scuti stars

Since CoRoT observations unveiled the very low amplitude modes that form a flat plateau in the power spectrum structure of delta Scuti stars, the nature of this phenomenon, including the possibility of spurious signals due to the light curve analysis, has been a matter of long-standing scientific debate. We contribute to this debate by finding the structural parameters of a sample of four delta Scuti stars, CID 546, CID 3619, CID 8669, and KIC 5892969, and looking for a possible relation between these stars' structural parameters and their power spectrum structure. For the purposes of characterization, we developed a method of studying and analysing the power spectrum with high precision and have applied it to both CoRoT and Kepler light curves. We obtain the best estimates to date of these stars' structural parameters. Moreover, we observe that the power spectrum structure depends on the inclination, oblateness, and convective efficiency of each star. Our results suggest that the power spectrum structure is real and is possibly formed by 2-period island modes and chaotic modes

Enters algebraics i treballs de Kummer sobre l’últim teorema de Fermat

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2018, Director: Luis Victor Dieulefait[en] Fermat’s Last Theorem asserts that the equation $x^{n} + y^{n}= x^{n}$ has not non-zero integral solutions $x, y, z$ for $n \geq 3$. In this project we study the Kummer’s proof of the first case of the Theorem along with developing the basic tools of the algebraic number theory. This first case is that the exponent $n$ in the equation is a so-called regular prime and n does not divide any of $x, y, z$

Tackling IoT ultra large scale systems: Fog computing in support of hierarchical emergent behaviors

The Internet of Things (IoT) marks a phase transition in the evolution of the Internet, distinguished by a massive connectivity and the interaction with the physical world. The organic evolution of IoT requires the consideration of three dimensions: scale, organization, and context. These dimensions are particularly relevant in Ultra Large Scale Systems (ULSS), of which autonomous vehicles is a prime example. Fog Computing is well positioned to support contextual awareness and communication, critical for ULSS. The design and orchestration of ULSS require fresh approaches, new organizing principles. A recent paper proposed Hierarchical Emergent Behaviors (HEB), an architecture that builds on established concepts of emergent behaviors and hierarchical decomposition and organization. HEB’s local rules induce emergent behaviors, i.e., useful behaviors not explicitly programmed. In this chapter we take a first step to validate HEB concepts through the study of two basic self-driven car “primitives”: exiting a platoon formation, and maneuvering in anticipation of obstacles beyond the range of on-board sensors. Fog nodes provide the critical contextual information required.Damian Roca work was supported by a Doctoral Scholarship provided by Fundación La Caixa. This work has been supported by the Spanish Government (Severo Ochoa grants SEV2015-0493) and by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316-P).Peer ReviewedPostprint (author's final draft

Fog function virtualization: A flexible solution for IoT applications

The Internet of Things applications must carefully assess certain crucial factors such as the real-time and largely distributed nature of the “things”. Fog Computing provides an architecture to satisfy those requirements through nodes located from near the “things” till the edge. The problem comes with the integration of the Fog nodes into current infrastructures. This process requires the development of complex software solutions and prevents Fog growth. In this paper we propose three innovations to enhance Fog: (i) a new orchestration policy, (ii) the creation of constellations of nodes, and (iii) Fog Function Virtualization (FFV). All together will complement Fog to reach its true potential as a generic scalable platform, running multiple IoT applications simultaneously. Deploying a new service is reduced to the development of the application code, fact that brings the democratization of the Fog Computing paradigm through ease of deployment and cost reduction.The authors thanks Rodolfo Milito for his insightful comments and revisions. Damian Roca work was supported by a Doctoral Scholarship provided by Fundación La Caixa. Josue V. Quiroga work was supported by a Doctoral Scholarship provided by the Mexican National Council of Science and Technology (CONACyT). This work has been supported by the Spanish Government (Severo Ochoa grants SEV2015-0493) and by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316-P).Peer ReviewedPostprint (author's final draft

TRUFAS, a wavelet based algorithm for the rapid detection of planetary transits

Aims: We describe a fast, robust and automatic detection algorithm, TRUFAS, and apply it to data that are being expected from the CoRoT mission. Methods: The procedure proposed for the detection of planetary transits in light curves works in two steps: 1) a continuous wavelet transformation of the detrended light curve with posterior selection of the optimum scale for transit detection, and 2) a period search in that selected wavelet transformation. The detrending of the light curves are based on Fourier filtering or a discrete wavelet transformation. TRUFAS requires the presence of at least 3 transit events in the data. Results: The proposed algorithm is shown to identify reliably and quickly the transits that had been included in a standard set of 999 light curves that simulate CoRoT data. Variations in the pre-processing of the light curves and in the selection of the scale of the wavelet transform have only little effect on TRUFAS' results. Conclusions: TRUFAS is a robust and quick transit detection algorithm, especially well suited for the analysis of very large volumes of data from space or ground-based experiments, with long enough durations for the target-planets to produce multiple transit events.Comment: 9 pages, 10 figures, accepted by A&