Formal Verification of a Gain Scheduling Control Scheme

Gain scheduling is a commonly used closed-loop control approach for safety critical non-linear systems, such as commercial gas turbine engines. It is preferred over more advanced control strategies due to a known route to certification. Nonetheless, the stability of the system is hard to prove analytically, and consequently, safety and airworthiness is achieved by burdensome extensive testing. Model checking can aid in bringing down development costs of such a control system and simultaneously improve safety by providing guarantees on properties of embedded control systems. Due to model-checking exhaustive verification capabilities, it has long been recognised that coverage and error-detection rate can be increased compared to traditional testing methods. However, the statespace explosion is still a major computational limitation when applying model-checking to verify dynamic system behaviour. A practical methodology to incrementally design and formally verify control system requirements for a gain scheduling scheme is demonstrated in this paper, overcoming the computational constraints traditionally imposed by model checking. In this manner, the gain-scheduled controller can be efficiently and safely generated with the aid of the model checker

Automated context aware composition of Advanced Telecom Services for environmental early warnings

This paper presents one of the main components of a framework for automated composition of Advanced Telecom Services for environmental early Warnings. The framework, called AUTO, is composed by three main modules: a request processing module that transforms natural language and context information into a planning instance; the automated planning module, based on PELEA, an architecture for planning and execution; and the Service Execution Environment Advance Telecom Services. This paper focuses on the description of the translation of the user request in natural language and his context into planning instances. These planning instances represent service composition tasks based on Automated Planning. The advantages of this approach, like the automatic inclusion of context and user preferences in the composition of services, will be presented. Also, the current implementation will be described and some experimentation will prove the viability of AUTO

Lights out: training RL agents robust to temporary blindness

Agents trained with DQN rely on an observation at each timestep to decide what action to take next. However, in real world applications observations can change or be missing entirely. Examples of this could be a light bulb breaking down, or the wallpaper in a certain room changing. While these situations change the actual observation, the underlying optimal policy does not change. Because of this we want our agent to continue taking actions until it receives a (recognized) observation again. To achieve this we introduce a combination of a neural network architecture that uses hidden representations of the observations and a novel n-step loss function. Our implementation is able to withstand location based blindness stretches longer than the ones it was trained on, and therefore shows robustness to temporary blindness. For access to our implementation, please email Nathan, Marije, or Pau

Implementation of an Online Feedback-Path-Modelling Active Noise Control System

Active Noise Control (ANC) systems have proved to be a very efficient way to reduce low-frequency acoustic noise. On this domain, passive techniques like enclosures, barriers and silencers tend to be relatively large, costly and ineffective. Although many studies and articles have been published in order to improve performance and stability, the implementation of a real-time, stable and robust system still faces several theoretical and practical challenges

Energy optimization in wireless sensor networks based on genetic algorithms

Wireless sensor is a consolidated technology with high potential in the Internet of Things. However, some open issues must be tackled in order to leverage the whole potential of this technology. One of the challenges is the energy consumption. Many algorithms have been proposed for saving energy. However these approaches use a mono-objective evaluation and the contradiction between optimization parameters values is not considered. Besides these approaches don't offer a unique solution. This paper describes MOR4WSN an algorithm based in NSGA-II for selecting the best sensor distribution as well as a mechanism for optimization of results. Experimental evaluation shows promising results in terms of lifetime maximization

The Long and Short of Nuclear Effective Field Theory Expansions

Nonperturbative effective field theory calculations for NN scattering seem to break down at rather low momenta. By examining several toy models, we clarify how effective field theory expansions can in general be used to properly separate long- and short-range effects. We find that one-pion exchange has a large effect on the scattering phase shift near poles in the amplitude, but otherwise can be treated perturbatively. Analysis of a toy model that reproduces 1S0 NN scattering data rather well suggests that failures of effective field theories for momenta above the pion mass can be due to short-range physics rather than the treatment of pion exchange. We discuss the implications this has for extending the applicability of effective field theories.Comment: 22 pages, 9 figures, references corrected, minor modification

Evaluation of

The use of software in the educational system has significantly improve the process of learning of the students. Today most schools adopt their curriculum model using software; oriented application that educational improvements and bonding of the technological world with education. In this article the JAWS tool is evaluated at the Basic Education School Specialized Blind and Deaf of Machala city, in which we will present the educational contribution that has provided the JAWS software, Job Access With Speech to students with disabilities visual. The research was conducted within the framework of a quantitative study, obtaining data through surveys and the application of standard ISO/IEC 9126 quality based on the characteristics of software USAbility. The result of the research showed that students have improved their skills by using this system

Low Energy Theorems For Nucleon-Nucleon Scattering

Low energy theorems are derived for the coefficients of the effective range expansion in s-wave nucleon-nucleon scattering valid to leading order in an expansion in which both $m_\pi$ and $1/a$ (where $a$ is the scattering length) are treated as small mass scales. Comparisons with phase shift data, however, reveal a pattern of gross violations of the theorems for all coefficients in both the $^1S_0$ and $^3S_1$ channels. Analogous theorems are developed for the energy dependence $\epsilon$ parameter which describes $^3S_1 - ^3D_1$ mixing. These theorems are also violated. These failures strongly suggest that the physical value of $m_\pi$ is too large for the chiral expansion to be valid in this context. Comparisons of $m_\pi$ with phenomenological scales known to arise in the two-nucleon problem support this conjecture.Comment: 12 pages, 1 figure, 1 table; appendix added to discuss behavior in chiral limit; minor revisions including revised figure reference to recent work adde

Star-unitary transformations. From dynamics to irreversibility and stochastic behavior

We consider a simple model of a classical harmonic oscillator coupled to a field. In standard approaches Langevin-type equations for {\it bare} particles are derived from Hamiltonian dynamics. These equations contain memory terms and are time-reversal invariant. In contrast the phenomenological Langevin equations have no memory terms (they are Markovian equations) and give a time evolution split in two branches (semigroups), each of which breaks time symmetry. A standard approach to bridge dynamics with phenomenology is to consider the Markovian approximation of the former. In this paper we present a formulation in terms of {\it dressed} particles, which gives exact Markovian equations. We formulate dressed particles for Poincar\'e nonintegrable systems, through an invertible transformation operator \Lam introduced by Prigogine and collaborators. \Lam is obtained by an extension of the canonical (unitary) transformation operator $U$ that eliminates interactions for integrable systems. Our extension is based on the removal of divergences due to Poincar\'e resonances, which breaks time-symmetry. The unitarity of $U$ is extended to ``star-unitarity'' for \Lam. We show that \Lam-transformed variables have the same time evolution as stochastic variables obeying Langevin equations, and that \Lam-transformed distribution functions satisfy exact Fokker-Planck equations. The effects of Gaussian white noise are obtained by the non-distributive property of \Lam with respect to products of dynamical variables. Therefore our method leads to a direct link between dynamics of Poincar\'e nonintegrable systems, probability and stochasticity.Comment: 24 pages, no figures. Made more connections with other work. Clarified ideas on irreversibilit